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Sample records for reservoir performance predictions

  1. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Martin J.; Orr, Franklin M.

    1999-05-17

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1997 - September 1998 under the second year of a three-year grant from the Department of Energy on the "Prediction of Gas Injection Performance for Heterogeneous Reservoirs." The research effort is an integrated study of the factors affecting gas injection, from the pore scale to the field scale, and involves theoretical analysis, laboratory experiments, and numerical simulation. The original proposal described research in four areas: (1) Pore scale modeling of three phase flow in porous media; (2) Laboratory experiments and analysis of factors influencing gas injection performance at the core scale with an emphasis on the fundamentals of three phase flow; (3) Benchmark simulations of gas injection at the field scale; and (4) Development of streamline-based reservoir simulator. Each state of the research is planned to provide input and insight into the next stage, such that at the end we should have an integrated understanding of the key factors affecting field scale displacements.

  2. Prediction of the thermohydraulic performance of porous-media reservoirs for compressed-air energy storage

    Energy Technology Data Exchange (ETDEWEB)

    Wiles, L.E.; McCann, R.A.

    1981-09-01

    The numerical modeling capability that has been developed at the Pacific Northwest Laboratory (PNL) for the prediction of the thermohydraulic performance of porous media reservoirs for compressed air energy storage (CAES) is described. The capability of the numerical models was demonstrated by application to a variety of parametric analyses and the support analyses for the CAES porous media field demonstration program. The demonstration site analyses include calculations for the displacement of aquifer water to develop the air storage zone, the potential for water coning, thermal development in the reservoir, and the dehydration of the near-wellbore region. Unique features of the demonstration site reservoir that affect the thermohydraulic performance are identified and contrasted against the predicted performance for conditions that would be considered more typical of a commercial CAES site.

  3. Incorporating Scale-Dependent Fracture Stiffness for Improved Reservoir Performance Prediction

    Science.gov (United States)

    Crawford, B. R.; Tsenn, M. C.; Homburg, J. M.; Stehle, R. C.; Freysteinson, J. A.; Reese, W. C.

    2017-12-01

    We present a novel technique for predicting dynamic fracture network response to production-driven changes in effective stress, with the potential for optimizing depletion planning and improving recovery prediction in stress-sensitive naturally fractured reservoirs. A key component of the method involves laboratory geomechanics testing of single fractures in order to develop a unique scaling relationship between fracture normal stiffness and initial mechanical aperture. Details of the workflow are as follows: tensile, opening mode fractures are created in a variety of low matrix permeability rocks with initial, unstressed apertures in the micrometer to millimeter range, as determined from image analyses of X-ray CT scans; subsequent hydrostatic compression of these fractured samples with synchronous radial strain and flow measurement indicates that both mechanical and hydraulic aperture reduction varies linearly with the natural logarithm of effective normal stress; these stress-sensitive single-fracture laboratory observations are then upscaled to networks with fracture populations displaying frequency-length and length-aperture scaling laws commonly exhibited by natural fracture arrays; functional relationships between reservoir pressure reduction and fracture network porosity, compressibility and directional permeabilities as generated by such discrete fracture network modeling are then exported to the reservoir simulator for improved naturally fractured reservoir performance prediction.

  4. Reservoir characterization and performance predictions for the E.N. Woods lease

    Energy Technology Data Exchange (ETDEWEB)

    Aka-Milan, Francis A.

    2000-07-07

    The task of this work was to evaluate the past performance of the E.N. WOODS Unit and to forecast its future economic performance by taking into consideration the geology, petrophysics and production history of the reservoir. The Decline Curve Analysis feature of the Appraisal of Petroleum Properties including Taxation Systems (EDAPT) software along with the Production Management Systems (PMS) software were used to evaluate the original volume of hydrocarbon in place and estimate the reserve. The Black Oil Simulator (BOAST II) was then used to model the waterflooding operation and estimate the incremental oil production attributable to the water injection. BOAST II was also used to predict future performance of the reservoir.

  5. HIGH RESOLUTION PREDICTION OF GAS INJECTION PROCESS PERFORMANCE FOR HETEROGENEOUS RESERVOIRS

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    Franklin M. Orr, Jr.

    2004-05-01

    This final technical report describes and summarizes results of a research effort to investigate physical mechanisms that control the performance of gas injection processes in heterogeneous reservoirs and to represent those physical effects in an efficient way in simulations of gas injection processes. The research effort included four main lines of research: (1) Efficient compositional streamline methods for 3D flow; (2) Analytical methods for one-dimensional displacements; (3) Physics of multiphase flow; and (4) Limitations of streamline methods. In the first area, results are reported that show how the streamline simulation approach can be applied to simulation of gas injection processes that include significant effects of transfer of components between phases. In the second area, the one-dimensional theory of multicomponent gas injection processes is extended to include the effects of volume change as components change phase. In addition an automatic algorithm for solving such problems is described. In the third area, results on an extensive experimental investigation of three-phase flow are reported. The experimental results demonstrate the impact on displacement performance of the low interfacial tensions between the gas and oil phases that can arise in multicontact miscible or near-miscible displacement processes. In the fourth area, the limitations of the streamline approach were explored. Results of an experimental investigation of the scaling of the interplay of viscous, capillary, and gravity forces are described. In addition results of a computational investigation of the limitations of the streamline approach are reported. The results presented in this report establish that it is possible to use the compositional streamline approach in many reservoir settings to predict performance of gas injection processes. When that approach can be used, it requires substantially less (often orders of magnitude) computation time than conventional finite difference

  6. Geologic CO2 Sequestration: Predicting and Confirming Performance in Oil Reservoirs and Saline Aquifers

    Science.gov (United States)

    Johnson, J. W.; Nitao, J. J.; Newmark, R. L.; Kirkendall, B. A.; Nimz, G. J.; Knauss, K. G.; Ziagos, J. P.

    2002-05-01

    Reducing anthropogenic CO2 emissions ranks high among the grand scientific challenges of this century. In the near-term, significant reductions can only be achieved through innovative sequestration strategies that prevent atmospheric release of large-scale CO2 waste streams. Among such strategies, injection into confined geologic formations represents arguably the most promising alternative; and among potential geologic storage sites, oil reservoirs and saline aquifers represent the most attractive targets. Oil reservoirs offer a unique "win-win" approach because CO2 flooding is an effective technique of enhanced oil recovery (EOR), while saline aquifers offer immense storage capacity and widespread distribution. Although CO2-flood EOR has been widely used in the Permian Basin and elsewhere since the 1980s, the oil industry has just recently become concerned with the significant fraction of injected CO2 that eludes recycling and is therefore sequestered. This "lost" CO2 now has potential economic value in the growing emissions credit market; hence, the industry's emerging interest in recasting CO2 floods as co-optimized EOR/sequestration projects. The world's first saline aquifer storage project was also catalyzed in part by economics: Norway's newly imposed atmospheric emissions tax, which spurred development of Statoil's unique North Sea Sleipner facility in 1996. Successful implementation of geologic sequestration projects hinges on development of advanced predictive models and a diverse set of remote sensing, in situ sampling, and experimental techniques. The models are needed to design and forecast long-term sequestration performance; the monitoring techniques are required to confirm and refine model predictions and to ensure compliance with environmental regulations. We have developed a unique reactive transport modeling capability for predicting sequestration performance in saline aquifers, and used it to simulate CO2 injection at Sleipner; we are now

  7. Neuro-Simulation Tool for Enhanced Oil Recovery Screening and Reservoir Performance Prediction

    Directory of Open Access Journals (Sweden)

    Soheil Bahrekazemi

    2017-09-01

    Full Text Available Assessment of the suitable enhanced oil recovery method in an oilfield is one of the decisions which are made prior to the natural drive production mechanism. In some cases, having in-depth knowledge about reservoir’s rock, fluid properties, and equipment is needed as well as economic evaluation. Both putting such data into simulation and its related consequent processes are generally very time consuming and costly.  In order to reduce study cases, an appropriate tool is required for primary screening prior to any operations being performed, to which leads reduction of time in design of ether pilot section or production under field condition. In this research, two different and useful screening tools are presented through a graphical user interface. The output of just over 900 simulations and verified screening criteria tables were employed to design the mentioned tools. Moreover, by means of gathered data and development of artificial neural networks, two dissimilar screening tools for proper assessment of suitable enhanced oil recovery method were finally introduced. The first tool is about the screening of enhanced oil recovery process based on published tables/charts and the second one which is Neuro-Simulation tool, concerns economical evaluation of miscible and immiscible injection of carbon dioxide, nitrogen and natural gas into the reservoir. Both of designed tools are provided in the form of a graphical user interface by which the user, can perceive suitable method through plot of oil recovery graph during 20 years of production, costs of gas injection per produced barrel, cumulative oil production, and finally, design the most efficient scenario.

  8. Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

    Science.gov (United States)

    Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

    2016-04-01

    Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of

  9. Prediction of reservoir compaction and surface subsidence

    Energy Technology Data Exchange (ETDEWEB)

    De Waal, J.A.; Smits, R.M.M.

    1988-06-01

    A new loading-rate-dependent compaction model for unconsolidated clastic reservoirs is presented that considerably improves the accuracy of predicting reservoir rock compaction and surface subsidence resulting from pressure depletion in oil and gas fields. The model has been developed on the basis of extensive laboratory studies and can be derived from a theory relating compaction to time-dependent intergranular friction. The procedure for calculating reservoir compaction from laboratory measurements with the new model is outlined. Both field and laboratory compaction behaviors appear to be described by one single normalized, nonlinear compaction curve. With the new model, the large discrepancies usually observed between predictions based on linear compaction models and actual (nonlinear) field behavior can be explained.

  10. Improved characterization of reservoir behavior by integration of reservoir performances data and rock type distributions

    Energy Technology Data Exchange (ETDEWEB)

    Davies, D.K.; Vessell, R.K. [David K. Davies & Associates, Kingwood, TX (United States); Doublet, L.E. [Texas A& M Univ., College Station, TX (United States)] [and others

    1997-08-01

    An integrated geological/petrophysical and reservoir engineering study was performed for a large, mature waterflood project (>250 wells, {approximately}80% water cut) at the North Robertson (Clear Fork) Unit, Gaines County, Texas. The primary goal of the study was to develop an integrated reservoir description for {open_quotes}targeted{close_quotes} (economic) 10-acre (4-hectare) infill drilling and future recovery operations in a low permeability, carbonate (dolomite) reservoir. Integration of the results from geological/petrophysical studies and reservoir performance analyses provide a rapid and effective method for developing a comprehensive reservoir description. This reservoir description can be used for reservoir flow simulation, performance prediction, infill targeting, waterflood management, and for optimizing well developments (patterns, completions, and stimulations). The following analyses were performed as part of this study: (1) Geological/petrophysical analyses: (core and well log data) - {open_quotes}Rock typing{close_quotes} based on qualitative and quantitative visualization of pore-scale features. Reservoir layering based on {open_quotes}rock typing {close_quotes} and hydraulic flow units. Development of a {open_quotes}core-log{close_quotes} model to estimate permeability using porosity and other properties derived from well logs. The core-log model is based on {open_quotes}rock types.{close_quotes} (2) Engineering analyses: (production and injection history, well tests) Material balance decline type curve analyses to estimate total reservoir volume, formation flow characteristics (flow capacity, skin factor, and fracture half-length), and indications of well/boundary interference. Estimated ultimate recovery analyses to yield movable oil (or injectable water) volumes, as well as indications of well and boundary interference.

  11. Why do Reservoir Computing Networks Predict Chaotic Systems so Well?

    Science.gov (United States)

    Lu, Zhixin; Pathak, Jaideep; Girvan, Michelle; Hunt, Brian; Ott, Edward

    Recently a new type of artificial neural network, which is called a reservoir computing network (RCN), has been employed to predict the evolution of chaotic dynamical systems from measured data and without a priori knowledge of the governing equations of the system. The quality of these predictions has been found to be spectacularly good. Here, we present a dynamical-system-based theory for how RCN works. Basically a RCN is thought of as consisting of three parts, a randomly chosen input layer, a randomly chosen recurrent network (the reservoir), and an output layer. The advantage of the RCN framework is that training is done only on the linear output layer, making it computationally feasible for the reservoir dimensionality to be large. In this presentation, we address the underlying dynamical mechanisms of RCN function by employing the concepts of generalized synchronization and conditional Lyapunov exponents. Using this framework, we propose conditions on reservoir dynamics necessary for good prediction performance. By looking at the RCN from this dynamical systems point of view, we gain a deeper understanding of its surprising computational power, as well as insights on how to design a RCN. Supported by Army Research Office Grant Number W911NF1210101.

  12. Effect of reservoir heterogeneity on air injection performance in a light oil reservoir

    Directory of Open Access Journals (Sweden)

    Hu Jia

    2018-03-01

    Full Text Available Air injection is a good option to development light oil reservoir. As well-known that, reservoir heterogeneity has great effect for various EOR processes. This also applies to air injection. However, oil recovery mechanisms and physical processes for air injection in heterogeneous reservoir with dip angle are still not well understood. The reported setting of reservoir heterogeneous for physical model or simulation model of air injection only simply uses different-layer permeability of porous media. In practice, reservoir heterogeneity follows the principle of geostatistics. How much of contrast in permeability actually challenges the air injection in light oil reservoir? This should be investigated by using layered porous medial settings of the classical Dykstra-Parsons style. Unfortunately, there has been no work addressing this issue for air injection in light oil reservoir. In this paper, Reservoir heterogeneity is quantified based on the use of different reservoir permeability distribution according to classical Dykstra-Parsons coefficients method. The aim of this work is to investigate the effect of reservoir heterogeneity on physical process and production performance of air injection in light oil reservoir through numerical reservoir simulation approach. The basic model is calibrated based on previous study. Total eleven pseudo compounders are included in this model and ten complexity of reactions are proposed to achieve the reaction scheme. Results show that oil recovery factor is decreased with the increasing of reservoir heterogeneity both for air and N2 injection from updip location, which is against the working behavior of air injection from updip location. Reservoir heterogeneity sometimes can act as positive effect to improve sweep efficiency as well as enhance production performance for air injection. High O2 content air injection can benefit oil recovery factor, also lead to early O2 breakthrough in heterogeneous reservoir. Well

  13. Performance Analysis of Depleted Oil Reservoirs for Underground Gas Storage

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    Dr. C.I.C. Anyadiegwu

    2014-02-01

    Full Text Available The performance of underground gas storage in depleted oil reservoir was analysed with reservoir Y-19, a depleted oil reservoir in Southern region of the Niger Delta. Information on the geologic and production history of the reservoir were obtained from the available field data of the reservoir. The verification of inventory was done to establish the storage capacity of the reservoir. The plot of the well flowing pressure (Pwf against the flow rate (Q, gives the deliverability of the reservoir at various pressures. Results of the estimated properties signified that reservoir Y-19 is a good candidate due to its storage capacity and its flow rate (Q of 287.61 MMscf/d at a flowing pressure of 3900 psig

  14. Reservoir Inflow Prediction under GCM Scenario Downscaled by Wavelet Transform and Support Vector Machine Hybrid Models

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    Gusfan Halik

    2015-01-01

    Full Text Available Climate change has significant impacts on changing precipitation patterns causing the variation of the reservoir inflow. Nowadays, Indonesian hydrologist performs reservoir inflow prediction according to the technical guideline of Pd-T-25-2004-A. This technical guideline does not consider the climate variables directly, resulting in significant deviation to the observation results. This research intends to predict the reservoir inflow using the statistical downscaling (SD of General Circulation Model (GCM outputs. The GCM outputs are obtained from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR Reanalysis. A new proposed hybrid SD model named Wavelet Support Vector Machine (WSVM was utilized. It is a combination of the Multiscale Principal Components Analysis (MSPCA and nonlinear Support Vector Machine regression. The model was validated at Sutami Reservoir, Indonesia. Training and testing were carried out using data of 1991–2008 and 2008–2012, respectively. The results showed that MSPCA produced better extracting data than PCA. The WSVM generated better reservoir inflow prediction than the one of technical guideline. Moreover, this research also applied WSVM for future reservoir inflow prediction based on GCM ECHAM5 and scenario SRES A1B.

  15. Carbonate reservoir characterization with lithofacies clustering and porosity prediction

    International Nuclear Information System (INIS)

    Al Moqbel, Abdulrahman; Wang, Yanghua

    2011-01-01

    One of the objectives in reservoir characterization is to quantitatively or semi-quantitatively map the spatial distribution of its heterogeneity and related properties. With the availability of 3D seismic data, artificial neural networks are capable of discovering the nonlinear relationship between seismic attributes and reservoir parameters. For a target carbonate reservoir, we adopt a two-stage approach to conduct characterization. First, we use an unsupervised neural network, the self-organizing map method, to classify the reservoir lithofacies. Then we apply a supervised neural network, the back-propagation algorithm, to quantitatively predict the porosity of the carbonate reservoir. Based on porosity maps at different time levels, we interpret the target reservoir vertically related to three depositional phases corresponding to, respectively, a lowstand system tract before sea water immersion, a highstand system tract when water covers organic deposits and a transition zone for the sea level falling. The highstand system is the most prospective zone, given the organic content deposited during this stage. The transition zone is also another prospective feature in the carbonate depositional system due to local build-ups

  16. Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.

    Science.gov (United States)

    Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

    2014-07-01

    Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Towards pattern generation and chaotic series prediction with photonic reservoir computers

    Science.gov (United States)

    Antonik, Piotr; Hermans, Michiel; Duport, François; Haelterman, Marc; Massar, Serge

    2016-03-01

    Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.

  18. Prediction of Hydrocarbon Reservoirs Permeability Using Support Vector Machine

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    R. Gholami

    2012-01-01

    Full Text Available Permeability is a key parameter associated with the characterization of any hydrocarbon reservoir. In fact, it is not possible to have accurate solutions to many petroleum engineering problems without having accurate permeability value. The conventional methods for permeability determination are core analysis and well test techniques. These methods are very expensive and time consuming. Therefore, attempts have usually been carried out to use artificial neural network for identification of the relationship between the well log data and core permeability. In this way, recent works on artificial intelligence techniques have led to introduce a robust machine learning methodology called support vector machine. This paper aims to utilize the SVM for predicting the permeability of three gas wells in the Southern Pars field. Obtained results of SVM showed that the correlation coefficient between core and predicted permeability is 0.97 for testing dataset. Comparing the result of SVM with that of a general regression neural network (GRNN revealed that the SVM approach is faster and more accurate than the GRNN in prediction of hydrocarbon reservoirs permeability.

  19. A Novel Method for Performance Analysis of Compartmentalized Reservoirs

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    Shahamat Mohammad Sadeq

    2016-05-01

    Full Text Available This paper presents a simple analytical model for performance analysis of compartmentalized reservoirs producing under Constant Terminal Rate (CTR and Constant Terminal Pressure (CTP. The model is based on the well-known material balance and boundary dominated flow equations and is written in terms of capacitance and resistance of a production and a support compartment. These capacitance and resistance terms account for a combination of reservoir parameters which enable the developed model to be used for characterizing such systems. In addition to considering the properties contrast between the two reservoir compartments, the model takes into account existence of transmissibility barriers with the use of resistance terms. The model is used to analyze production performance of unconventional reservoirs, where the multistage fracturing of horizontal wells effectively creates a Stimulated Reservoir Volume (SRV with an enhanced permeability surrounded by a non-stimulated region. It can also be used for analysis of compartmentalized conventional reservoirs. The analytical solutions provide type curves through which the controlling reservoirs parameters of a compartmentalized system can be estimated. The contribution of the supporting compartment is modeled based on a boundary dominated flow assumption. The transient behaviour of the support compartment is captured by application of “distance of investigation” concept. The model shows that depletion of the production and support compartments exhibit two unit slopes on a log-log plot of pressure versus time for CTR. For CTP, however, the depletions display two exponential declines. The depletion signatures are separated by transition periods, which depend on the contribution of the support compartment (i.e. transient or boundary dominated flow. The developed equations can be implemented easily in a spreadsheet application, and are corroborated with the use of a numerical simulation. The study

  20. Operational Precipitation prediction in Support of Real-Time Flash Flood Prediction and Reservoir Management

    Science.gov (United States)

    Georgakakos, K. P.

    2006-05-01

    The presentation will outline the implementation and performance evaluation of a number of national and international projects pertaining to operational precipitation estimation and prediction in the context of hydrologic warning systems and reservoir management support. In all cases, uncertainty measures of the estimates and predictions are an integral part of the precipitation models. Outstanding research issues whose resolution is likely to lead to improvements in the operational environment are presented. The presentation draws from the experience of the Hydrologic Research Center (http://www.hrc-lab.org) prototype implementation projects at the Panama Canal, Central America, Northern California, and South-Central US. References: Carpenter, T.M, and K.P. Georgakakos, "Discretization Scale Dependencies of the Ensemble Flow Range versus Catchment Area Relationship in Distributed Hydrologic Modeling," Journal of Hydrology, 2006, in press. Carpenter, T.M., and K.P. Georgakakos, "Impacts of Parametric and Radar Rainfall Uncertainty on the Ensemble Streamflow Simulations of a Distributed Hydrologic Model," Journal of Hydrology, 298, 202-221, 2004. Georgakakos, K.P., Graham, N.E., Carpenter, T.M., Georgakakos, A.P., and H. Yao, "Integrating Climate- Hydrology Forecasts and Multi-Objective Reservoir Management in Northern California," EOS, 86(12), 122,127, 2005. Georgakakos, K.P., and J.A. Sperfslage, "Operational Rainfall and Flow Forecasting for the Panama Canal Watershed," in The Rio Chagres: A Multidisciplinary Profile of a Tropical Watershed, R.S. Harmon, ed., Kluwer Academic Publishers, The Netherlands, Chapter 16, 323-334, 2005. Georgakakos, K. P., "Analytical results for operational flash flood guidance," Journal of Hydrology, doi:10.1016/j.jhydrol.2005.05.009, 2005.

  1. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    Energy Technology Data Exchange (ETDEWEB)

    Mohan Kelkar

    2002-03-31

    The West Carney Field in Lincoln County, Oklahoma is one of few newly discovered oil fields in Oklahoma. Although profitable, the field exhibits several unusual characteristics. These include decreasing water-oil ratios, decreasing gas-oil ratios, decreasing bottomhole pressures during shut-ins in some wells, and transient behavior for water production in many wells. This report explains the unusual characteristics of West Carney Field based on detailed geological and engineering analyses. We propose a geological history that explains the presence of mobile water and oil in the reservoir. The combination of matrix and fractures in the reservoir explains the reservoir's flow behavior. We confirm our hypothesis by matching observed performance with a simulated model and develop procedures for correlating core data to log data so that the analysis can be extended to other, similar fields where the core coverage may be limited.

  2. Gas condensate reservoir performance : part 1 : fluid characterization

    Energy Technology Data Exchange (ETDEWEB)

    Thomas, F.B.; Bennion, D.B. [Hycal Energy Research Laboratories Ltd., Calgary, AB (Canada); Andersen, G. [ChevronTexaco, Calgary, AB (Canada)

    2006-07-01

    Phase behaviour in gas condensate reservoirs is sensitive to changes in pressure and temperature, which can lead to significant errors in fluid characterization. The challenging task of characterizing in situ fluids in gas condensate reservoirs was discussed with reference to the errors that occur as a result of the complex coupling between phase behavior and geology. This paper presented techniques for reservoir sampling and characterization and proposed methods for minimizing errors. Errors are often made in the classification of dew point systems because engineering criteria does not accurately represent the phase behavior of the reservoir. For example, the fluid of a certain condensate yield may be categorized as a wet gas rather than a retrograde condensate fluid. It was noted that the liquid yield does not dictate whether the fluid is condensate or wet gas, but rather where the reservoir temperature is situated in the pressure temperature phase loop. In order to proceed with a viable field development plan and optimization, the reservoir fluid must be understood. Given that gas productivity decreases with liquid drop out in the near wellbore region, capillary pressure plays a significant role in retrograde reservoirs. It was noted that well understood parameters will lead to a better assessment of the amount of hydrocarbon in place, the rate at which the resource can be produced and optimization strategies as the reservoir matures. It was concluded that multi-rate sampling is the best method to use in sampling fluids since the liquid yield changes as a function of rate. Although bottom-hole sampling in gas condensate reservoirs may be problematic, it should always be performed to address any concerns for liquid-solid separation. Produced fluids typically reveal a specific signature that informs the operator of in situ properties. This paper presented examples that pertain to wet versus retrograde condensate behavior and the presence of an oil zone. The

  3. Performance of a system of reservoirs on futuristic front

    Science.gov (United States)

    Saha, Satabdi; Roy, Debasri; Mazumdar, Asis

    2017-10-01

    Application of simulation model HEC-5 to analyze the performance of the DVC Reservoir System (a multipurpose system with a network of five reservoirs and one barrage) on the river Damodar in Eastern India in meeting projected future demand as well as controlling flood for synthetically generated future scenario is addressed here with a view to develop an appropriate strategy for its operation. Thomas-Fiering model (based on Markov autoregressive model) has been adopted for generation of synthetic scenario (monthly streamflow series) and subsequently downscaling of modeled monthly streamflow to daily values was carried out. The performance of the system (analysed on seasonal basis) in terms of `Performance Indices' (viz., both quantity based reliability and time based reliability, mean daily deficit, average failure period, resilience and maximum vulnerability indices) for the projected scenario with enhanced demand turned out to be poor compared to that for historical scenario. However, judicious adoption of resource enhancement (marginal reallocation of reservoir storage capacity) and demand management strategy (curtailment of projected high water requirements and trading off between demands) was found to be a viable option for improvement of the performance of the reservoir system appreciably [improvement being (1-51 %), (2-35 %), (16-96 %), (25-50 %), (8-36 %) and (12-30 %) for the indices viz., quantity based reliability, time based reliability, mean daily deficit, average failure period, resilience and maximum vulnerability, respectively] compared to that with normal storage and projected demand. Again, 100 % reliability for flood control for current as well as future synthetically generated scenarios was noted. The results from the study would assist concerned authority in successful operation of reservoirs in the context of growing demand and dwindling resource.

  4. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    Energy Technology Data Exchange (ETDEWEB)

    Mohan Kelkar

    2004-10-01

    West Carney field--one of the newest fields discovered in Oklahoma--exhibits many unique production characteristics. These characteristics include: (1) decreasing water-oil ratio; (2) decreasing gas-oil ratio followed by an increase; (3) poor prediction capability of the reserves based on the log data; and (4) low geological connectivity but high hydrodynamic connectivity. The purpose of this investigation is to understand the principal mechanisms affecting the production, and propose methods by which we can extend the phenomenon to other fields with similar characteristics. In our experimental investigation section, we present the data on surfactant injection in near well bore region. We demonstrate that by injecting the surfactant, the relative permeability of water could be decreased, and that of gas could be increased. This should result in improved gas recovery from the reservoir. Our geological analysis of the reservoir develops the detailed stratigraphic description of the reservoir. Two new stratigraphic units, previously unrecognized, are identified. Additional lithofacies are recognized in new core descriptions. Our engineering analysis has determined that well density is an important parameter in optimally producing Hunton reservoirs. It appears that 160 acre is an optimal spacing. The reservoir pressure appears to decline over time; however, recovery per well is only weakly influenced by the pressure. This indicates that additional opportunity to drill wells exists in relatively depleted fields. A simple material balance technique is developed to validate the recovery of gas, oil and water. This technique can be used to further extrapolate recoveries from other fields with similar field characteristics.

  5. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    Energy Technology Data Exchange (ETDEWEB)

    Mohan Kelkar

    2005-02-01

    Hunton formation in Oklahoma has displayed some unique production characteristics. These include high initial water-oil and gas-oil ratios, decline in those ratios over time and temporary increase in gas-oil ratio during pressure build up. The formation also displays highly complex geology, but surprising hydrodynamic continuity. This report addresses three key issues related specifically to West Carney Hunton field and, in general, to any other Hunton formation exhibiting similar behavior: (1) What is the primary mechanism by which oil and gas is produced from the field? (2) How can the knowledge gained from studying the existing fields can be extended to other fields which have the potential to produce? (3) What can be done to improve the performance of this reservoir? We have developed a comprehensive model to explain the behavior of the reservoir. By using available production, geological, core and log data, we are able to develop a reservoir model which explains the production behavior in the reservoir. Using easily available information, such as log data, we have established the parameters needed for a field to be economically successful. We provide guidelines in terms of what to look for in a new field and how to develop it. Finally, through laboratory experiments, we show that surfactants can be used to improve the hydrocarbons recovery from the field. In addition, injection of CO{sub 2} or natural gas also will help us recover additional oil from the field.

  6. Application of an expert system to optimize reservoir performance

    International Nuclear Information System (INIS)

    Gharbi, Ridha

    2005-01-01

    The main challenge of oil displacement by an injected fluid, such as in Enhanced Oil Recovery (EOR) processes, is to reduce the cost and improve reservoir performance. An optimization methodology, combined with an economic model, is implemented into an expert system to optimize the net present value of full field development with an EOR process. The approach is automated and combines an economic package and existing numerical reservoir simulators to optimize the design of a selected EOR process using sensitivity analysis. The EOR expert system includes three stages of consultations: (1) select an appropriate EOR process on the basis of the reservoir characteristics, (2) prepare appropriate input data sets to design the selected EOR process using existing numerical simulators, and (3) apply the discounted-cash-flow methods to the optimization of the selected EOR process to find out under what conditions at current oil prices this EOR process might be profitable. The project profitability measures were used as the decision-making variables in an iterative approach to optimize the design of the EOR process. The economic analysis is based on the estimated recovery, residual oil in-place, oil price, and operating costs. Two case studies are presented for two reservoirs that have already been produced to their economic limits and are potential candidates for surfactant/polymer flooding, and carbon-dioxide flooding, respectively, or otherwise subject to abandonment. The effect of several design parameters on the project profitability of these EOR processes was investigated

  7. The Hybrid of Classification Tree and Extreme Learning Machine for Permeability Prediction in Oil Reservoir

    KAUST Repository

    Prasetyo Utomo, Chandra

    2011-06-01

    Permeability is an important parameter connected with oil reservoir. Predicting the permeability could save millions of dollars. Unfortunately, petroleum engineers have faced numerous challenges arriving at cost-efficient predictions. Much work has been carried out to solve this problem. The main challenge is to handle the high range of permeability in each reservoir. For about a hundred year, mathematicians and engineers have tried to deliver best prediction models. However, none of them have produced satisfying results. In the last two decades, artificial intelligence models have been used. The current best prediction model in permeability prediction is extreme learning machine (ELM). It produces fairly good results but a clear explanation of the model is hard to come by because it is so complex. The aim of this research is to propose a way out of this complexity through the design of a hybrid intelligent model. In this proposal, the system combines classification and regression models to predict the permeability value. These are based on the well logs data. In order to handle the high range of the permeability value, a classification tree is utilized. A benefit of this innovation is that the tree represents knowledge in a clear and succinct fashion and thereby avoids the complexity of all previous models. Finally, it is important to note that the ELM is used as a final predictor. Results demonstrate that this proposed hybrid model performs better when compared with support vector machines (SVM) and ELM in term of correlation coefficient. Moreover, the classification tree model potentially leads to better communication among petroleum engineers concerning this important process and has wider implications for oil reservoir management efficiency.

  8. Geothermal reservoir simulation to enhance confidence in predictions for nuclear waste disposal

    International Nuclear Information System (INIS)

    Kneafsey, Timothy J.; Pruess, Karsten; O'Sullivan, Michael J.; Bodvarsson, Gudmundur S.

    2002-01-01

    Numerical simulation of geothermal reservoirs is useful and necessary in understanding and evaluating reservoir structure and behavior, designing field development, and predicting performance. Models vary in complexity depending on processes considered, heterogeneity, data availability, and study objectives. They are evaluated using computer codes written and tested to study single and multiphase flow and transport under nonisothermal conditions. Many flow and heat transfer processes modeled in geothermal reservoirs are expected to occur in anthropogenic thermal (AT) systems created by geologic disposal of heat-generating nuclear waste. We examine and compare geothermal systems and the AT system expected at Yucca Mountain, Nevada, and their modeling. Time frames and spatial scales are similar in both systems, but increased precision is necessary for modeling the AT system, because flow through specific repository locations will affect long-term ability radionuclide retention. Geothermal modeling experience has generated a methodology, used in the AT modeling for Yucca Mountain, yielding good predictive results if sufficient reliable data are available and an experienced modeler is involved. Codes used in geothermal and AT modeling have been tested extensively and successfully on a variety of analytical and laboratory problems

  9. A poroelastic reservoir model for predicting subsidence and mapping subsurface pressure fronts

    International Nuclear Information System (INIS)

    Du, J.; Olson, J.E.

    2001-01-01

    A forward model was constructed to numerically predict surface subsidence and reservoir compaction following the approach of Segall [Pure Appl. Phys. 139 (1992) 536]. A nucleus of poroelastic strain is numerically integrated over a rectangular prism assuming constant pressure change. This fundamental geometry allows a reservoir to be divided into many small cubic blocks in a manner similar to reservoir simulation. The subsidence and compaction effects of the pressure change throughout the reservoir are calculated by the superposition of results from each individual block. Using forward modeling, pressure boundary conditions can be acquired from pressure test data or reservoir simulation predictions. An inversion model also was developed that can track pressure fronts in a subsurface reservoir using surface displacements. The capability of the inversion model was demonstrated using synthetic examples of one-well and four-well cases with different layouts of surface observation locations. The impact of noise on the inversion result is also included

  10. Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

    DEFF Research Database (Denmark)

    Wang, Y.; Chen, H.; Rosbjerg, Dan

    2013-01-01

    In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which...... is developed by the Japan Meteorological Agency, was used to forecast rainfall with 5 days lead-time in the upper region of the Three Gorges Reservoir (TGR). A conceptual hydrological model, the Xinanjiang Model, has been set up to forecast the inflow flood of TGR by the Ministry of Water Resources Information...... season 2012 as example, real-time dynamic control of the FLWL was implemented by using the forecasted reservoir flood inflow as input. The forecasted inflow with 5 days lead-time rainfall forecast was evaluated by several performance indices, including the mean relative error of the volumetric reservoir...

  11. Validating predictions of evolving porosity and permeability in carbonate reservoir rocks exposed to CO2-brine

    Science.gov (United States)

    Smith, M. M.; Hao, Y.; Carroll, S.

    2017-12-01

    Improving our ability to better forecast the extent and impact of changes in porosity and permeability due to CO2-brine-carbonate reservoir interactions should lower uncertainty in long-term geologic CO2 storage capacity estimates. We have developed a continuum-scale reactive transport model that simulates spatial and temporal changes to porosity, permeability, mineralogy, and fluid composition within carbonate rocks exposed to CO2 and brine at storage reservoir conditions. The model relies on two primary parameters to simulate brine-CO2-carbonate mineral reaction: kinetic rate constant(s), kmineral, for carbonate dissolution; and an exponential parameter, n, relating porosity change to resulting permeability. Experimental data collected from fifteen core-flooding experiments conducted on samples from the Weyburn (Saskatchewan, Canada) and Arbuckle (Kansas, USA) carbonate reservoirs were used to calibrate the reactive-transport model and constrain the useful range of k and n values. Here we present the results of our current efforts to validate this model and the use of these parameter values, by comparing predictions of extent and location of dissolution and the evolution of fluid permeability against our results from new core-flood experiments conducted on samples from the Duperow Formation (Montana, USA). Agreement between model predictions and experimental data increase our confidence that these parameter ranges need not be considered site-specific but may be applied (within reason) at various locations and reservoirs. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  12. Possibility of predicting the water drive mechanism of oil bearing reservoirs before its exploitation

    Energy Technology Data Exchange (ETDEWEB)

    Cubric, S

    1971-10-01

    The study deals with the application of Van Everdingen and Hurst's method to prediction of water influx from aquifer into an oil-bearing part of a reservoir. The examples show an influence of the factors affecting the water influx (time, permeability, ratio of radii of the aquifer, and oil-bearing part of reservoir.)

  13. Gate valve performance prediction

    International Nuclear Information System (INIS)

    Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

    1994-01-01

    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  14. Fluvial facies reservoir productivity prediction method based on principal component analysis and artificial neural network

    Directory of Open Access Journals (Sweden)

    Pengyu Gao

    2016-03-01

    Full Text Available It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

  15. pressure analysis and fluid contact prediction for alpha reservoir

    African Journals Online (AJOL)

    HOD

    a pressure gradient profile such that the oil gradient line will intersect the hydrostatic line above the Water-Up-To. (WUT) line to define the OWC if present. The model was also calibrated with data from reservoirs with established contacts in the field. 3. RESULTS AND DISCUSSION. In the field, pressure typically increases ...

  16. Improved prediction of reservoir behavior through integration of quantitative geological and petrophysical data

    Energy Technology Data Exchange (ETDEWEB)

    Auman, J. B.; Davies, D. K.; Vessell, R. K.

    1997-08-01

    Methodology that promises improved reservoir characterization and prediction of permeability, production and injection behavior during primary and enhanced recovery operations was demonstrated. The method is based on identifying intervals of unique pore geometry by a combination of image analysis techniques and traditional petrophysical measurements to calculate rock type and estimate permeability and saturation. Results from a complex carbonate and sandstone reservoir were presented as illustrative examples of the versatility and high level of accuracy of this method in predicting reservoir quality. 16 refs., 5 tabs., 14 figs.

  17. High-Performance Modeling of Carbon Dioxide Sequestration by Coupling Reservoir Simulation and Molecular Dynamics

    KAUST Repository

    Bao, Kai

    2015-10-26

    The present work describes a parallel computational framework for carbon dioxide (CO2) sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel high-performance-computing (HPC) systems. In this framework, a parallel reservoir simulator, reservoir-simulation toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, whereas the MD simulations are performed to provide the required physical parameters. Technologies from several different fields are used to make this novel coupled system work efficiently. One of the major applications of the framework is the modeling of large-scale CO2 sequestration for long-term storage in subsurface geological formations, such as depleted oil and gas reservoirs and deep saline aquifers, which has been proposed as one of the few attractive and practical solutions to reduce CO2 emissions and address the global-warming threat. Fine grids and accurate prediction of the properties of fluid mixtures under geological conditions are essential for accurate simulations. In this work, CO2 sequestration is presented as a first example for coupling reservoir simulation and MD, although the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical processes in the future. Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability is observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well-demonstrated with several experiments with hundreds of millions to one billion cells. To the best of our knowledge, the present work represents the first attempt to couple reservoir simulation and molecular simulation for large-scale modeling. Because of the complexity of

  18. Multinomial Logistic Regression & Bootstrapping for Bayesian Estimation of Vertical Facies Prediction in Heterogeneous Sandstone Reservoirs

    Science.gov (United States)

    Al-Mudhafar, W. J.

    2013-12-01

    Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly

  19. Improving reservoir performance using new 'smart' well technology

    International Nuclear Information System (INIS)

    Roggensack, W.D.; Matthews, C.M.

    1997-01-01

    The technologies that were available in the past to improve reservoir performance include 3-D seismic, coiled tubing, horizontal wells, and PCP's. Future enabling technologies will also include multi-lateral wells, 'smart' wells, underbalanced drilling, and downhole fluids processing. A description of 'smart' well technology was given, defined as well completions which facilitate downhole monitoring and control of production to achieve maximum reserves recovery. The current development for 'smart' wells is focused on offshore and subsea wells for marginal field development and work-over mitigation, with the emphasis in system design for production control of horizontal and multi-lateral wells. Basic 'smart' well configuration, instrumentation and monitoring systems, applications of 'smart' well technology in the Western Canadian Sedimentary Basin, and future developments and applications for the technology in general, were also discussed. 30 figs

  20. High-performance modeling of CO2 sequestration by coupling reservoir simulation and molecular dynamics

    KAUST Repository

    Bao, Kai

    2013-01-01

    The present work describes a parallel computational framework for CO2 sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel HPC systems. In this framework, a parallel reservoir simulator, Reservoir Simulation Toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, while the molecular dynamics simulations are performed to provide the required physical parameters. Numerous technologies from different fields are employed to make this novel coupled system work efficiently. One of the major applications of the framework is the modeling of large scale CO2 sequestration for long-term storage in the subsurface geological formations, such as depleted reservoirs and deep saline aquifers, which has been proposed as one of the most attractive and practical solutions to reduce the CO2 emission problem to address the global-warming threat. To effectively solve such problems, fine grids and accurate prediction of the properties of fluid mixtures are essential for accuracy. In this work, the CO2 sequestration is presented as our first example to couple the reservoir simulation and molecular dynamics, while the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical process in the future. Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability are observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well demonstrated with several experiments with hundreds of millions to a billion cells. To our best knowledge, the work represents the first attempt to couple the reservoir simulation and molecular simulation for large scale modeling. Due to the complexity of the subsurface systems

  1. The geological model calibration - Learnings from integration of reservoir geology and field performance - Example from the upper carboniferous reservoirs of the Southern North Sea

    NARCIS (Netherlands)

    Moscariello, A.; Hoof, T.B. van; Kunakbayeva, G.; Veen, J.H. ten; Belt, F. van den; Twerda, A.; Peters, L.; Davis, P.; Williams, H.

    2013-01-01

    The Geological Model Calibration - Learnings from Integration of Reservoir Geology and Field Performance: example from the Upper Carboniferous Reservoirs of the Southern North Sea. Copyright © (2012) by the European Association of Geoscientists & Engineers All rights reserved.

  2. Performance Prediction Toolkit

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-25

    The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes, cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few

  3. Development of a neural fuzzy system for advanced prediction of dew point pressure in gas condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Nowroozi, Saeed; Hashemipour, Hasan; Schaffie, Mahin [Department of Chemical Engineering, Shahid Bahonar University of Kerman (Iran); ERC, Shahid Bahonar University of Kerman (Iran); Ranjbar, Mohammad [Department of Mining Engineering, Shahid Bahonar University of Kerman (Iran); ERC, Shahid Bahonar University of Kerman (Iran)

    2009-03-15

    Dew point pressure is one of the most critical quantities for characterizing a gas condensate reservoir. So, accurate determination of this property has been the main challenge in reservoir development and management. The experimental determination of dew point pressure in PVT cell is often difficult especially in case of lean retrograde gas condensate. Empirical correlations and some equations of state can be used to calculate reservoir fluid properties. Empirical correlations do not have ability to reliable duplicate the temperature behavior of constant composition fluids. Equations of state have convergence problem and need to be tuned against some experimental data. Complexity, non-linearity and vagueness are some reservoir parameter characteristic which can be propagated simply by intelligent system. With the advantage of fuzzy sets in knowledge representation and the high capacity of neural nets (NNs) in learning knowledge expressed in data, in this paper a neural fuzzy system(NFS) is proposed to predict dew point pressure of gas condensate reservoir. The model was developed using 110 measurements of dew point pressure. The performance of the model is compared against performance of some of the most accurate and general correlations for dew point pressure calculation. From the results of this study, it can be pointed out that this novel method is more accurate and reliable with the mean square error of 0.058%, 0.074% and 0.044% for training, validation and test processes, respectively. (author)

  4. PREDICTION OF RESERVOIR FLOW RATE OF DEZ DAM BY THE PROBABILITY MATRIX METHOD

    Directory of Open Access Journals (Sweden)

    Mohammad Hashem Kanani

    2012-12-01

    Full Text Available The data collected from the operation of existing storage reservoirs, could offer valuable information for the better allocation and management of fresh water rates for future use to mitigation droughts effect. In this paper the long-term Dez reservoir (IRAN water rate prediction is presented using probability matrix method. Data is analyzed to find the probability matrix of water rates in Dez reservoir based on the previous history of annual water entrance during the past and present years(40 years. The algorithm developed covers both, the overflow and non-overflow conditions in the reservoir. Result of this study shows that in non-overflow conditions the most exigency case is equal to 75%. This means that, if the reservoir is empty (the stored water is less than 100 MCM this year, it would be also empty by 75% next year. The stored water in the reservoir would be less than 300 MCM by 85% next year if the reservoir is empty this year. This percentage decreases to 70% next year if the water of reservoir is less than 300 MCM this year. The percentage also decreases to 5% next year if the reservoir is full this year. In overflow conditions the most exigency case is equal to 75% again. The reservoir volume would be less than 150 MCM by 90% next year, if it is empty this year. This percentage decreases to 70% if its water volume is less than 300 MCM and 55% if the water volume is less than 500 MCM this year. Result shows that too, if the probability matrix of water rates to a reservoir is multiplied by itself repeatedly; it converges to a constant probability matrix, which could be used to predict the long-term water rate of the reservoir. In other words, the probability matrix of series of water rates is changed to a steady probability matrix in the course of time, which could reflect the hydrological behavior of the watershed and could be easily used for the long-term prediction of water storage in the down stream reservoirs.

  5. Well performance relationships in heavy foamy oil reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, R.; Mahadevan, J. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Tulsa Univ., Tulsa, OK (United States)

    2008-10-15

    The viscosities and thermodynamic properties of heavy oils are different from conventional oils. Heavy oil reservoirs have foamy behaviour and the gas/oil interface stabilizes in the presence of asphaltenes. In the case of conventional oils, gas evolves from the solution when the formation pressure reaches the bubble point pressure. This study modelled the fluid properties of heavy foamy oils and their influence on the inflow performance relationship (IPR). An expression for inflow performance in heavy oil was developed by including the properties of foamy oil into a space averaged flow equation assuming pseudo-steady state conditions. The unique feature of this study was that the density, formation volume factor and solution gas-oil ratio were modelled as functions of entrained gas fraction. The newly developed expression for inflow performance of foamy oils may also be used to model conventional oil inflow by setting the entrained gas fraction to zero in the fluid property models. The results of the inflow performance of foamy oil and conventional oil were compared and an outflow performance relationship was calculated. The study showed that the inflow performance in foamy oil is influenced by entrained gas. The surface flow rates and bottom-hole flow rates are also influenced by the presence of entrained gas, with heavy foamy oil showing a higher volumetric production rate than conventional oil. The outflow performance curve depended on the fluid properties of the foamy oil. A nodal analysis of the well performance showed that the conventional calculation methods underestimate the production from foamy oil wells because they do not consider the effect of entrained gas which lowers density and improves the mobility of foamy oil. 14 refs., 2 tabs., 20 figs., 1 appendix.

  6. Assessing reservoir performance risk in CO2 storage projects

    International Nuclear Information System (INIS)

    Bowden, A.R.; Rigg, A.

    2005-01-01

    One of the main issues for researchers involved with geological storage of carbon dioxide (CO 2 ) has been the development of a proper methodology to assess and compare alternative CO 2 injection projects on the basis of risk. Consideration needs to be given to technical aspects, such as the risk of leakage and the effectiveness of the intended reservoir, as well as less tangible aspects such as the value and safety of geological storage of CO 2 , and potential impacts on the community and environment. The Geological Disposal of Carbon Dioxide (GEODISC), was a research program of the Australian Petroleum Cooperative Research Centre which identified 56 potential environmentally sustainable sites for CO 2 injection (ESSCIs) within Australia. Several studies were carried out, involving detailed evaluation of the suitability of 4 selected sites, including Dongara, Petrel, Gippsland and Carnarvon. The GEODISC program included a risk assessment research module which required a complete and quantified risk assessment of CO 2 injection as a storage option. Primary goals were to assess the risk of leakage, to assess the effectiveness of the intended reservoir, and to assess negative consequences to facilitate comparison of alternative sites. This paper discussed the background and risk assessment model. Key performance indicators (KPIs) were also developed to address the purpose of risk assessment. It was concluded that the RISQUE method is an appropriate approach and that potential injection projects can be measured against six KPIs including containment; effectiveness; self-funding potential; wider community benefits; community safety and community amenity. 6 refs., 3 tabs., 3 figs

  7. Real-time reservoir operation considering non-stationary inflow prediction

    Science.gov (United States)

    Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

    2011-12-01

    Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

  8. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Watney, W.L.

    1994-12-01

    Reservoirs in the Lansing-Kansas City limestone result from complex interactions among paleotopography (deposition, concurrent structural deformation), sea level, and diagenesis. Analysis of reservoirs and surface and near-surface analogs has led to developing a {open_quotes}strandline grainstone model{close_quotes} in which relative sea-level stabilized during regressions, resulting in accumulation of multiple grainstone buildups along depositional strike. Resulting stratigraphy in these carbonate units are generally predictable correlating to inferred topographic elevation along the shelf. This model is a valuable predictive tool for (1) locating favorable reservoirs for exploration, and (2) anticipating internal properties of the reservoir for field development. Reservoirs in the Lansing-Kansas City limestones are developed in both oolitic and bioclastic grainstones, however, re-analysis of oomoldic reservoirs provides the greatest opportunity for developing bypassed oil. A new technique, the {open_quotes}Super{close_quotes} Pickett crossplot (formation resistivity vs. porosity) and its use in an integrated petrophysical characterization, has been developed to evaluate extractable oil remaining in these reservoirs. The manual method in combination with 3-D visualization and modeling can help to target production limiting heterogeneities in these complex reservoirs and moreover compute critical parameters for the field such as bulk volume water. Application of this technique indicates that from 6-9 million barrels of Lansing-Kansas City oil remain behind pipe in the Victory-Northeast Lemon Fields. Petroleum geologists are challenged to quantify inferred processes to aid in developing rationale geologically consistent models of sedimentation so that acceptable levels of prediction can be obtained.

  9. Nonlinear Model Predictive Control for Oil Reservoirs Management

    DEFF Research Database (Denmark)

    Capolei, Andrea

    expensive gradient computation by using high-order ESDIRK (Explicit Singly Diagonally Implicit Runge-Kutta) temporal integration methods and continuous adjoints. The high order integration scheme allows larger time steps and therefore faster solution times. We compare gradient computation by the continuous...... gradient-based optimization and the required gradients are computed by the adjoint method. We propose the use of efficient high order implicit time integration methods for the solution of the forward and the adjoint equations of the dynamical model. The Ensemble Kalman filter is used for data assimilation...... equivalent strategy is not justified for the particular case studied in this paper. The third contribution of this thesis is a mean-variance method for risk mitigation in production optimization of oil reservoirs. We introduce a return-risk bicriterion objective function for the profit-risk tradeoff...

  10. Reservoir rock permeability prediction using support vector regression in an Iranian oil field

    International Nuclear Information System (INIS)

    Saffarzadeh, Sadegh; Shadizadeh, Seyed Reza

    2012-01-01

    Reservoir permeability is a critical parameter for the evaluation of hydrocarbon reservoirs. It is often measured in the laboratory from reservoir core samples or evaluated from well test data. The prediction of reservoir rock permeability utilizing well log data is important because the core analysis and well test data are usually only available from a few wells in a field and have high coring and laboratory analysis costs. Since most wells are logged, the common practice is to estimate permeability from logs using correlation equations developed from limited core data; however, these correlation formulae are not universally applicable. Recently, support vector machines (SVMs) have been proposed as a new intelligence technique for both regression and classification tasks. The theory has a strong mathematical foundation for dependence estimation and predictive learning from finite data sets. The ultimate test for any technique that bears the claim of permeability prediction from well log data is the accurate and verifiable prediction of permeability for wells where only the well log data are available. The main goal of this paper is to develop the SVM method to obtain reservoir rock permeability based on well log data. (paper)

  11. Prediction of tectonic stresses and fracture networks with geomechanical reservoir models

    International Nuclear Information System (INIS)

    Henk, A.; Fischer, K.

    2014-09-01

    This project evaluates the potential of geomechanical Finite Element (FE) models for the prediction of in situ stresses and fracture networks in faulted reservoirs. Modeling focuses on spatial variations of the in situ stress distribution resulting from faults and contrasts in mechanical rock properties. In a first methodological part, a workflow is developed for building such geomechanical reservoir models and calibrating them to field data. In the second part, this workflow was applied successfully to an intensively faulted gas reservoir in the North German Basin. A truly field-scale geomechanical model covering more than 400km 2 was built and calibrated. It includes a mechanical stratigraphy as well as a network of 86 faults. The latter are implemented as distinct planes of weakness and allow the fault-specific evaluation of shear and normal stresses. A so-called static model describes the recent state of the reservoir and, thus, after calibration its results reveal the present-day in situ stress distribution. Further geodynamic modeling work considers the major stages in the tectonic history of the reservoir and provides insights in the paleo stress distribution. These results are compared to fracture data and hydraulic fault behavior observed today. The outcome of this project confirms the potential of geomechanical FE models for robust stress and fracture predictions. The workflow is generally applicable and can be used for modeling of any stress-sensitive reservoir.

  12. Prediction of tectonic stresses and fracture networks with geomechanical reservoir models

    Energy Technology Data Exchange (ETDEWEB)

    Henk, A.; Fischer, K. [TU Darmstadt (Germany). Inst. fuer Angewandte Geowissenschaften

    2014-09-15

    This project evaluates the potential of geomechanical Finite Element (FE) models for the prediction of in situ stresses and fracture networks in faulted reservoirs. Modeling focuses on spatial variations of the in situ stress distribution resulting from faults and contrasts in mechanical rock properties. In a first methodological part, a workflow is developed for building such geomechanical reservoir models and calibrating them to field data. In the second part, this workflow was applied successfully to an intensively faulted gas reservoir in the North German Basin. A truly field-scale geomechanical model covering more than 400km{sup 2} was built and calibrated. It includes a mechanical stratigraphy as well as a network of 86 faults. The latter are implemented as distinct planes of weakness and allow the fault-specific evaluation of shear and normal stresses. A so-called static model describes the recent state of the reservoir and, thus, after calibration its results reveal the present-day in situ stress distribution. Further geodynamic modeling work considers the major stages in the tectonic history of the reservoir and provides insights in the paleo stress distribution. These results are compared to fracture data and hydraulic fault behavior observed today. The outcome of this project confirms the potential of geomechanical FE models for robust stress and fracture predictions. The workflow is generally applicable and can be used for modeling of any stress-sensitive reservoir.

  13. A Structurally Simplified Hybrid Model of Genetic Algorithm and Support Vector Machine for Prediction of Chlorophyll a in Reservoirs

    Directory of Open Access Journals (Sweden)

    Jieqiong Su

    2015-04-01

    Full Text Available With decreasing water availability as a result of climate change and human activities, analysis of the influential factors and variation trends of chlorophyll a has become important to prevent reservoir eutrophication and ensure water supply safety. In this paper, a structurally simplified hybrid model of the genetic algorithm (GA and the support vector machine (SVM was developed for the prediction of monthly concentration of chlorophyll a in the Miyun Reservoir of northern China over the period from 2000 to 2010. Based on the influence factor analysis, the four most relevant influence factors of chlorophyll a (i.e., total phosphorus, total nitrogen, permanganate index, and reservoir storage were extracted using the method of feature selection with the GA, which simplified the model structure, making it more practical and efficient for environmental management. The results showed that the developed simplified GA-SVM model could solve nonlinear problems of complex system, and was suitable for the simulation and prediction of chlorophyll a with better performance in accuracy and efficiency in the Miyun Reservoir.

  14. A history match of the 1993 ESAGD pilot performance in the Peace River reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Ding, M.; Whale, L. [Shell Canada Ltd., Calgary, AB (Canada)

    2006-07-01

    This paper described a history matching procedure conducted to examine the performance of an enhanced steam assisted gravity drainage (ESAGD) pilot project originally initiated in 1993. The ESAGD process began as a conventional SAGD process, but when the steam chambers were fully developed, a pressure differential between the chambers was added to increase the steam drive component. A numerical planning simulation predicted cumulative average bitumen production rates of between 80 m{sup 3} per day per well pair. However, the actual average day bitumen rate was 22.5 m{sup 3} per day. The oil to steam ratio was 0.1. Final estimated recovery efficiency rates were estimated at 10 per cent. The simulated history match deviated in its predictions after the application of the pressure differential between the 2 well pairs during the ESAGD process. Results from a series of sensitivity studies demonstrated that well performance relied on the presence of high water saturation zones and on the petrophysical properties assigned within the model for horizontal and vertical permeability. The history match demonstrated that the majority of the bitumen produced during the pilot scheme came from the highly permeable bottom zone of the reservoir. It was concluded that steam zones did not rise far above the basal zone, and was limited by the vertical permeability of the reservoir. 6 refs., 2 tabs., 13 figs.

  15. Cengklik Reservoir Performance and Its Role for Drought Mitigation

    Directory of Open Access Journals (Sweden)

    Yovi Hardiyanto

    2015-05-01

    Full Text Available Water availability problem is encountered by Cengklik Reservoir due to drought disaster in the current year. It causes irrigation water crisis over 850 hectares crop field which of 350 hectares were not cultivated. The risk that must be faced by farmers is decrease in potential productivity, losses about more than 2.5 billion. Therefore, it needs technical solution to reduce this drought disaster risk. To obtain an alternative solution against water availability problem for drought disaster mitigation, this research used optimization of reservoir standard operating simulation. It applies field area of rice or Palawija at the second and/or the third cultivation season as decision variable, maximum productivity value as objective function, irrigation water demand as parameter depending on specified alternative crop pattern and schedule, and several constraints comprising 100% of reservoir reliability, all field is irrigated at the first and second season in which maximum non-irrigated crop field at the third cultivation season are 300 hectares. The tool used to conduct optimization was Microsoft Excel software. The result showed that crop pattern considered as an alternative solution against water availability problem in Cengklik reservoir is paddy-paddy-maize at the early of November II cultivated over 433 hectares and 1524 hectares. Risk reduction reached 9.33% in term of reservoir reliability, 23.61% in term of irrigated area, and 27.29% in term of vulnerability towards water availability crisis.

  16. Performance of thermal solvent process in Athabasca reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Das, Swapan [Marathon Oil (Canada)

    2011-07-01

    In the petroleum industry, due to depletion of conventional resources and high demand operators are looking into heavy oil and bitumen production. Different recovery methods exist, some of them based on heating the reservoir and others on the use of solvent. Thermal solvent process is a combination of both: a small amount of heat is used to maintain a solvent vapor phase in the reservoir. This process has advantages, solvent is mostly recycled which increases bitumen recovery efficiency and reduces the need for fresh solvent, but it also poses challenges, such as maintaining a vapor chamber and the fact that solvent solubility might be affected by heating. The aim of this paper is to discuss these issues. Simulations and field tests were conducted on bitumen in the the Athabasca region. This paper presented a thermal solvent process and its application's results in Athabasca reservoir.

  17. Exploitation and Optimization of Reservoir Performance in Hunton Formation, Oklahoma, Budget Period I, Class Revisit

    Energy Technology Data Exchange (ETDEWEB)

    Kelkar, Mohan

    2002-04-02

    This report explains the unusual characteristics of West Carney Field based on detailed geological and engineering analyses. A geological history that explains the presence of mobile water and oil in the reservoir was proposed. The combination of matrix and fractures in the reservoir explains the reservoir?s flow behavior. We confirm our hypothesis by matching observed performance with a simulated model and develop procedures for correlating core data to log data so that the analysis can be extended to other, similar fields where the core coverage may be limited.

  18. Results of Instrument Observations and Adaptive Prediction of Thermoabrasion of Banks of the Vilyui Reservoir

    International Nuclear Information System (INIS)

    Velikin, S. A.; Sobol’, I. S.; Sobol’, S. V.; Khokhlov, D. N.

    2013-01-01

    Quantitative data derived from observations of reformation of the thermoabrasive banks of the Viliyui Reservoir in Yakutia during the service period from 1972 through 2011, and results of analytical prediction of bank formations over the next 20 years for purposes of monitoring the ecological safety of this water body are presented

  19. Results of Instrument Observations and Adaptive Prediction of Thermoabrasion of Banks of the Vilyui Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Velikin, S. A. [Vilyuisk Permafrost Scientific-Research Station, Institute of Permafrost Science, Siberian Division of the Russian Academy of Sciences (Russian Federation); Sobol' , I. S.; Sobol' , S. V.; Khokhlov, D. N. [Nizhnii Novgorod State Architectural and Civil-Engineering University (Russian Federation)

    2013-11-15

    Quantitative data derived from observations of reformation of the thermoabrasive banks of the Viliyui Reservoir in Yakutia during the service period from 1972 through 2011, and results of analytical prediction of bank formations over the next 20 years for purposes of monitoring the ecological safety of this water body are presented.

  20. Production performance laws of vertical wells by volume fracturing in CBM reservoirs

    Directory of Open Access Journals (Sweden)

    Liehui Zhang

    2017-05-01

    Full Text Available Volume fracturing technology has been widely applied in the development of coalbed methane (CBM reservoirs. As for the stimulated reservoir volume (SRV created by volume fracturing, the seepage laws of fluids are described more accurately and rationally in the rectangular composite model than in the traditional radial composite model. However, the rectangular composite model considering SRV cannot be solved using the analytical or semi-analytical function method, and its solution from the linear flow model has larger errors. In view of this, SRV areas of CBM reservoirs were described by means of dual-medium model in this paper. The complex CBM migration mechanisms were investigated comprehensively, including adsorption, desorption, diffusion and seepage. A well testing model for rectangular composite fracturing wells in CBM reservoirs based on unsteady-state diffusion was built and solved using the boundary element method combined with Laplace transformation, Stehfest numerical inversion and computer programming technology. Thus, production performance laws of CBM reservoirs were clarified. The flow regimes of typical well testing curves were divided and the effects on change laws of production performance from the boundary size of gas reservoirs, permeability of volume fractured areas, adsorption gas content, reservoir permeability and SRV size were analyzed. Eventually, CBM reservoirs after the volume fracturing stimulation were described more accurately and rationally. This study provides a theoretical basis for a better understanding of the CBM migration laws and an approach to evaluating and developing CBM reservoirs efficiently and rationally.

  1. The role of predictive uncertainty in the operational management of reservoirs

    Directory of Open Access Journals (Sweden)

    E. Todini

    2014-09-01

    Full Text Available The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc. or via stochastic (generally stochastic dynamic programming approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.

  2. The influence of reservoir heterogeneities on geothermal doublet performance

    NARCIS (Netherlands)

    Doddema, Leon

    2012-01-01

    SUMMARY The current main problem with deep geothermal energy in the Netherlands is the uncertainty in terms of attainable flow rate and life time. The goal of this research is therefore modeling a geothermal doublet in a heterogeneous reservoir, using a

  3. Intermittent reservoir daily-inflow prediction using lumped and ...

    Indian Academy of Sciences (India)

    For the present case study considered, both MLR and ARIMA models performed ... is to be remembered that the transformation of ... Multi-linear regression; lumped and distributed data; time-series models; cause-effect ... flow data are short for adequate system study. ..... that the standard deviation, skewness, kurtosis.

  4. Facies and porosity origin of reservoirs: Case studies from the Cambrian Longwangmiao Formation of Sichuan Basin, China, and their implications on reservoir prediction

    Directory of Open Access Journals (Sweden)

    Anjiang Shen

    2018-02-01

    Full Text Available The dolostone of the Cambrian Longwangmiao Formation has been a significant gas exploration area in Sichuan Basin. In Gaoshiti-Moxi regions, a giant gas pool with thousands of billion cubic meters' reserve has been discovered. However, the origin of the reservoir and the distribution patterns are still disputed, eventually constraining the dolostone exploration of the Longwangmiao Formation. This paper focuses on the characteristics, origin, and distribution patterns of the dolostone reservoir in the Longwangmiao Formation based on: the outcrop geological survey, cores, thin-sections observation, reservoir geochemical characteristics study, and reservoir simulation experiments. As a result, two realizations were acquired: (1 The Cambrian Longwangmiao Formation could be divided into upper and lower part in Sichuan Basin. Based on the two parts of the Longwangmiao Formation, two lithofacies paleogeographic maps were generated. In addition, the carbonate slope sedimentary models were established. The grainstone shoals are mainly distributed in the shallow slope of the upper part in the Longwangmiao Formation. (2 The grainstone shoals are the developing basis of the dolostone reservoir in the Longwangmiao Formation. Moreover, the contemporaneous dissolution was a critical factor of grainstone shoal reservoir development in the Longwangmiao Formation. Controlled by the exposure surface, the dissolution vugs are not only extensively distributed, but also successively developed along the contemporaneous pore zones. Hence, the distribution patterns could be predicted. The geological understandings of the origin of dolostone reservoir in the Longwangmiao Formation show that the reservoir distributed in the areas of karstification in the Gaoshiti-Moxi regions, as well as the widespread grainstone shoals in the whole basin, are the potential exploration targets. Keywords: Sichuan Basin, Longwangmiao Formation, Carbonate slope, Dolograinstone shoal

  5. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    DeBey, T.M.

    1989-01-01

    The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

  6. Evaluation, prediction, and protection of water quality in Danjiangkou Reservoir, China

    Directory of Open Access Journals (Sweden)

    Xiao-kang Xin

    2015-01-01

    Full Text Available The water quality in the Danjiangkou Reservoir has attracted considerable attention from the Chinese public and government since the announcement of the Middle Route of the South to North Water Diversion Project (SNWDP, which commenced transferring water in 2014. Integrated research on the evaluation, prediction, and protection of water quality in the Danjiangkou Reservoir was carried out in this study in order to improve environmental management. Based on 120 water samples, wherein 17 water quality indices were measured at 20 monitoring sites, a single factor evaluation method was used to evaluate the current status of water quality. The results show that the main indices influencing the water quality in the Danjiangkou Reservoir are total phosphorus (TP, permanganate index (CODMn, dissolved oxygen (DO, and five-day biochemical oxygen demand (BOD5, and the concentrations of TP, BOD5, ammonia nitrogen (NH3–N, CODMn, DO, and anionic surfactant (Surfa do not reach the specified standard levels in the tributaries. Seasonal Mann–Kendall tests indicated that the CODMn concentration shows a highly significant increasing trend, and the TP concentration shows a significant increasing trend in the Danjiangkou Reservoir. The distribution of the main water quality indices in the Danjiangkou Reservoir was predicted using a two-dimensional water quality numerical model, and showed that the sphere of influence from the tributaries can spread across half of the Han Reservoir if the pollutants are not controlled. Cluster analysis (CA results suggest that the Shending River is heavily polluted, that the Jianghe, Sihe, and Jianhe rivers are moderately polluted, and that they should be the focus of environmental remediation.

  7. Characterization and Prediction of the Gas Hydrate Reservoir at the Second Offshore Gas Production Test Site in the Eastern Nankai Trough, Japan

    Directory of Open Access Journals (Sweden)

    Machiko Tamaki

    2017-10-01

    Full Text Available Following the world’s first offshore production test that was conducted from a gas hydrate reservoir by a depressurization technique in 2013, the second offshore production test has been planned in the eastern Nankai Trough. In 2016, the drilling survey was performed ahead of the production test, and logging data that covers the reservoir interval were newly obtained from three wells around the test site: one well for geological survey, and two wells for monitoring surveys, during the production test. The formation evaluation using the well log data suggested that our target reservoir has a more significant heterogeneity in the gas hydrate saturation distribution than we expected, although lateral continuity of sand layers is relatively good. To evaluate the spatial distribution of gas hydrate, the integration analysis using well and seismic data was performed. The seismic amplitude analysis supports the lateral reservoir heterogeneity that has a significant positive correlation with the resistivity log data at the well locations. The spatial distribution of the apparent low-resistivity interval within the reservoir observed from log data was investigated by the P-velocity volume derived from seismic inversion. The integrated results were utilized for the pre-drill prediction of the reservoir quality at the producing wells. These approaches will reduce the risk of future commercial production from the gas hydrate reservoir.

  8. Prediction of fish biomass, harvest and prey--predator relations in reservoirs

    International Nuclear Information System (INIS)

    Jenkins, R.M.

    1977-01-01

    Regression analyses of the effect of total dissolved solids on fish standing crops in 166 reservoirs produced formulas with coefficients of determination of 0.63 to 0.81. These formulas provide indexes to average biotic conditions and help to identify stressed aquatic environments. Simple predictive formulas are also presented for clupeid crops in various reservoir types, as clupeids are the fishes most frequently impinged or entrained at southern power plants. A method of calculating the adequacy of the available prey crop in relation to the predator crop is advanced to further aid in identification of perturbed prey populations. Assessment of stress as reflected by changes in sport fishing success can also be approached by comparison of the predicted harvest potential with actual fish harvest data. Use of these predictive indexes is recommended until more elaborate models are developed to identify power plant effects

  9. Cased-hole log analysis and reservoir performance monitoring

    CERN Document Server

    Bateman, Richard M

    2015-01-01

    This book addresses vital issues, such as the evaluation of shale gas reservoirs and their production. Topics include the cased-hole logging environment, reservoir fluid properties; flow regimes; temperature, noise, cement bond, and pulsed neutron logging; and casing inspection. Production logging charts and tables are included in the appendices. The work serves as a comprehensive reference for production engineers with upstream E&P companies, well logging service company employees, university students, and petroleum industry training professionals. This book also: ·       Provides methods of conveying production logging tools along horizontal well segments as well as measurements of formation electrical resistivity through casing ·       Covers new information on fluid flow characteristics in inclined pipe and provides new and improved nuclear tool measurements in cased wells ·       Includes updates on cased-hole wireline formation testing  

  10. Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs

    Directory of Open Access Journals (Sweden)

    Zhengchao Xie

    2012-01-01

    Full Text Available Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult to model the growth of algae species. Recently, support vector machine (SVM was reported to have advantages of only requiring a small amount of samples, high degree of prediction accuracy, and long prediction period to solve the nonlinear problems. In this study, the SVM-based prediction and forecast models for phytoplankton abundance in Macau Storage Reservoir (MSR are proposed, in which the water parameters of pH, SiO2, alkalinity, bicarbonate (HCO3 -, dissolved oxygen (DO, total nitrogen (TN, UV254, turbidity, conductivity, nitrate, total nitrogen (TN, orthophosphate (PO4 3−, total phosphorus (TP, suspended solid (SS and total organic carbon (TOC selected from the correlation analysis of the 23 monthly water variables were included, with 8-year (2001–2008 data for training and the most recent 3 years (2009–2011 for testing. The modeling results showed that the prediction and forecast powers were estimated as approximately 0.76 and 0.86, respectively, showing that the SVM is an effective new way that can be used for monitoring algal bloom in drinking water storage reservoir.

  11. Asphaltene laboratory assessment of a heavy onshore reservoir during pressure, temperature and composition variations to predict asphaltene onset pressure

    Energy Technology Data Exchange (ETDEWEB)

    Bahrami, Peyman; Ahmadi, Yaser [Islamic Azad University, Tehran (Iran, Islamic Republic of); Kharrat, Riyaz [Petroleum University of Technology, Tehran (Iran, Islamic Republic of); Mahdavi, Sedigheh; James, Lesley [Memorial University of Newfoundland, Saint John' s (Canada)

    2015-02-15

    An Iranian heavy oil reservoir recently encountered challenges in oil production rate, and further investigation has proven that asphaltene precipitation was the root cause of this problem. In addition, CO{sub 2} gas injection could be an appropriate remedy to enhance the production of heavy crudes. In this study, high pressure-high temperature asphaltene precipitation experiments were performed at different temperatures and pressures to investigate the asphaltene phase behavior during the natural depletion process and CO{sub 2} gas injection. Compositional modeling of experimental data predicted onset points at different temperatures which determine the zone of maximum probability of asphaltene precipitation for the studied heavy oil reservoir. Also, the effect of CO{sub 2} gas injection was investigated as a function of CO{sub 2} concentration and pressure. It was found that a CO{sub 2}-oil ratio of 40% is the optimum for limiting precipitation to have the least formation damage and surface instrument contamination.

  12. Methodology for Analyzing and Predicting the Runoff and Sediment into a Reservoir

    Directory of Open Access Journals (Sweden)

    Chun-Feng Hao

    2017-06-01

    Full Text Available With the rapid economic growth in China, a large number of hydropower projects have been planned and constructed. The sediment deposition of the reservoirs is one of the most important disputes during the construction and operation, because there are many heavy sediment-laden rivers. The analysis and prediction of the runoff and sediment into a reservoir is of great significance for reservoir operation. With knowledge of the incoming runoff and sediment characteristics, the regulator can adjust the reservoir discharge to guarantee the water supply, and flush more sediment at appropriate times. In this study, the long-term characteristics of runoff and sediment, including trend, jump point, and change cycle, are analyzed using various statistical approaches, such as accumulated anomaly analysis, the Fisher ordered clustering method, and Maximum Entropy Spectral Analysis (MESA. Based on the characteristics, a prediction model is established using the Auto-Regressive Moving Average (ARIMA method. The whole analysis and prediction system is applied to The Three Gorges Project (TGP, one of the biggest hydropower-complex projects in the world. Taking hydrologic series from 1955 to 2010 as the research objectives, the results show that both the runoff and the sediment are decreasing, and the reduction rate of sediment is much higher. Runoff and sediment into the TGP display cyclic variations over time, with a cycle of about a decade, but catastrophe points for runoff and sediment appear in 1991 and 2001, respectively. Prediction models are thus built based on monthly average hydrologic series from 2003 to 2010. ARIMA (1, 1, 1 × (1, 1, 112 and ARIMA (0, 1, 1 × (0, 1, 112 are selected for the runoff and sediment predictions, respectively, and the parameters of the models are also calibrated. The analysis of autocorrelation coefficients and partial autocorrelation coefficients of the residuals indicates that the models built in this study are feasible

  13. EPRI MOV performance prediction program

    International Nuclear Information System (INIS)

    Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

    1994-01-01

    An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

  14. Uncertainties in reservoir performance forecasts; Estimativa de incertezas na previsao de desempenho de reservatorios

    Energy Technology Data Exchange (ETDEWEB)

    Loschiavo, Roberto

    1999-07-01

    Project economic evaluation as well as facilities design for oil exploration is, in general based on production forecast. Since production forecast depends on several parameters that are not completely known, one should take a probabilistic approach for reservoir modeling and numerical flow simulation. In this work, we propose a procedure to estimate probabilistic production forecast profiles based on the decision tree technique. The most influencing parameters of a reservoir model are identified identified and combined to generate a number of realizations of the reservoirs. The combination of each branch of the decision tree defines the probability associated to each reservoir model. A computer program was developed to automatically generate the reservoir models, submit them to the numerical simulator, and process the results. Parallel computing was used to improve the performance of the procedure. (author)

  15. Mineral content prediction for unconventional oil and gas reservoirs based on logging data

    Science.gov (United States)

    Maojin, Tan; Youlong, Zou; Guoyue

    2012-09-01

    Coal bed methane and shale oil &gas are both important unconventional oil and gas resources, whose reservoirs are typical non-linear with complex and various mineral components, and the logging data interpretation model are difficult to establish for calculate the mineral contents, and the empirical formula cannot be constructed due to various mineral. The radial basis function (RBF) network analysis is a new method developed in recent years; the technique can generate smooth continuous function of several variables to approximate the unknown forward model. Firstly, the basic principles of the RBF is discussed including net construct and base function, and the network training is given in detail the adjacent clustering algorithm specific process. Multi-mineral content for coal bed methane and shale oil &gas, using the RBF interpolation method to achieve a number of well logging data to predict the mineral component contents; then, for coal-bed methane reservoir parameters prediction, the RBF method is used to realized some mineral contents calculation such as ash, volatile matter, carbon content, which achieves a mapping from various logging data to multimineral. To shale gas reservoirs, the RBF method can be used to predict the clay content, quartz content, feldspar content, carbonate content and pyrite content. Various tests in coalbed and gas shale show the method is effective and applicable for mineral component contents prediction

  16. Reservoir Performance Under Future Climate For Basins With Different Hydrologic Sensitivities

    Science.gov (United States)

    Mateus, M. C.; Tullos, D. D.

    2013-12-01

    In addition to long-standing uncertainties related to variable inflows and market price of power, reservoir operators face a number of new uncertainties related to hydrologic nonstationarity, changing environmental regulations, and rapidly growing water and energy demands. This study investigates the impact, sensitivity, and uncertainty of changing hydrology on hydrosystem performance across different hydrogeologic settings. We evaluate the performance of reservoirs in the Santiam River basin, including a case study in the North Santiam Basin, with high permeability and extensive groundwater storage, and the South Santiam Basin, with low permeability, little groundwater storage and rapid runoff response. The modeling objective is to address the following study questions: (1) for the two hydrologic regimes, how does the flood management, water supply, and environmental performance of current reservoir operations change under future 2.5, 50 and 97.5 percentile streamflow projections; and (2) how much change in inflow is required to initiate a failure to meet downstream minimum or maximum flows in the future. We couple global climate model results with a rainfall-runoff model and a formal Bayesian uncertainty analysis to simulate future inflow hydrographs as inputs to a reservoir operations model. To evaluate reservoir performance under a changing climate, we calculate reservoir refill reliability, changes in flood frequency, and reservoir time and volumetric reliability of meeting minimum spring and summer flow target. Reservoir performance under future hydrology appears to vary with hydrogeology. We find higher sensitivity to floods for the North Santiam Basin and higher sensitivity to minimum flow targets for the South Santiam Basin. Higher uncertainty is related with basins with a more complex hydrologeology. Results from model simulations contribute to understanding of the reliability and vulnerability of reservoirs to a changing climate.

  17. High-Performance Modeling of Carbon Dioxide Sequestration by Coupling Reservoir Simulation and Molecular Dynamics

    KAUST Repository

    Bao, Kai; Yan, Mi; Allen, Rebecca; Salama, Amgad; Lu, Ligang; Jordan, Kirk E.; Sun, Shuyu; Keyes, David E.

    2015-01-01

    The present work describes a parallel computational framework for carbon dioxide (CO2) sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel high-performance-computing (HPC) systems

  18. Performance analysis for an irreversible variable temperature heat reservoir closed intercooled regenerated Brayton cycle

    International Nuclear Information System (INIS)

    Wang Wenhua; Chen Lingen; Sun Fengrui; Wu Chih

    2003-01-01

    In this paper, the theory of finite time thermodynamics is used in the performance analysis of an irreversible closed intercooled regenerated Brayton cycle coupled to variable temperature heat reservoirs. The analytical formulae for dimensionless power and efficiency, as functions of the total pressure ratio, the intercooling pressure ratio, the component (regenerator, intercooler, hot and cold side heat exchangers) effectivenesses, the compressor and turbine efficiencies and the thermal capacity rates of the working fluid and the heat reservoirs, the pressure recovery coefficients, the heat reservoir inlet temperature ratio, and the cooling fluid in the intercooler and the cold side heat reservoir inlet temperature ratio, are derived. The intercooling pressure ratio is optimized for optimal power and optimal efficiency, respectively. The effects of component (regenerator, intercooler and hot and cold side heat exchangers) effectivenesses, the compressor and turbine efficiencies, the pressure recovery coefficients, the heat reservoir inlet temperature ratio and the cooling fluid in the intercooler and the cold side heat reservoir inlet temperature ratio on optimal power and its corresponding intercooling pressure ratio, as well as optimal efficiency and its corresponding intercooling pressure ratio are analyzed by detailed numerical examples. When the heat transfers between the working fluid and the heat reservoirs are executed ideally, the pressure drop losses are small enough to be neglected and the thermal capacity rates of the heat reservoirs are infinite, the results of this paper replicate those obtained in recent literature

  19. An improved method for predicting brittleness of rocks via well logs in tight oil reservoirs

    Science.gov (United States)

    Wang, Zhenlin; Sun, Ting; Feng, Cheng; Wang, Wei; Han, Chuang

    2018-06-01

    There can be no industrial oil production in tight oil reservoirs until fracturing is undertaken. Under such conditions, the brittleness of the rocks is a very important factor. However, it has so far been difficult to predict. In this paper, the selected study area is the tight oil reservoirs in Lucaogou formation, Permian, Jimusaer sag, Junggar basin. According to the transformation of dynamic and static rock mechanics parameters and the correction of confining pressure, an improved method is proposed for quantitatively predicting the brittleness of rocks via well logs in tight oil reservoirs. First, 19 typical tight oil core samples are selected in the study area. Their static Young’s modulus, static Poisson’s ratio and petrophysical parameters are measured. In addition, the static brittleness indices of four other tight oil cores are measured under different confining pressure conditions. Second, the dynamic Young’s modulus, Poisson’s ratio and brittleness index are calculated using the compressional and shear wave velocity. With combination of the measured and calculated results, the transformation model of dynamic and static brittleness index is built based on the influence of porosity and clay content. The comparison of the predicted brittleness indices and measured results shows that the model has high accuracy. Third, on the basis of the experimental data under different confining pressure conditions, the amplifying factor of brittleness index is proposed to correct for the influence of confining pressure on the brittleness index. Finally, the above improved models are applied to formation evaluation via well logs. Compared with the results before correction, the results of the improved models agree better with the experimental data, which indicates that the improved models have better application effects. The brittleness index prediction method of tight oil reservoirs is improved in this research. It is of great importance in the optimization of

  20. A Reduced Order Model for Fast Production Prediction from an Oil Reservoir with a Gas Cap

    OpenAIRE

    Yang, Yichen

    2016-01-01

    Master's thesis in Petroleum geosciences engineering Economic evaluations are essential inputs for oil and gas field development decisions. These evaluations are critically dependent on the unbiased assessment of uncertainty in the future oil and gas production from wells. However, many production prediction techniques come at significant computational costs as they often require a very large number of highly detailed grid based reservoir simulations. In this study, we present an alter...

  1. Prediction of Geomechanical Properties from Thermal Conductivity of Low-Permeable Reservoirs

    Science.gov (United States)

    Chekhonin, Evgeny; Popov, Evgeny; Popov, Yury; Spasennykh, Mikhail; Ovcharenko, Yury; Zhukov, Vladislav; Martemyanov, Andrey

    2016-04-01

    A key to assessing a sedimentary basin's hydrocarbon prospect is correct reconstruction of thermal and structural evolution. It is impossible without adequate theory and reliable input data including among other factors thermal and geomechanical rock properties. Both these factors are also important in geothermal reservoirs evaluation and carbon sequestration problem. Geomechanical parameters are usually estimated from sonic logging and rare laboratory measurements, but sometimes it is not possible technically (low quality of the acoustic signal, inappropriate borehole and mud conditions, low core quality). No wonder that there are attempts to correlate the thermal and geomechanical properties of rock, but no one before did it with large amount of high quality thermal conductivity data. Coupling results of sonic logging and non-destructive non-contact thermal core logging opens wide perspectives for studying a relationship between the thermal and geomechanical properties. More than 150 m of full size cores have been measured at core storage with optical scanning technique. Along with results of sonic logging performed with Sonic Scanner in different wells drilled in low permeable formations in West Siberia (Russia) it provided us with unique data set. It was established a strong correlation between components of thermal conductivity (measured perpendicular and parallel to bedding) and compressional and shear acoustic velocities in Bazhen formation. As a result, prediction of geomechanical properties via thermal conductivity data becomes possible, corresponding results was demonstrated. The work was supported by the Russian Ministry of Education and Science, project No. RFMEFI58114X0008.

  2. Predicting petrophysical properties by simultaneous inversion of seismic and reservoir engineering data

    Science.gov (United States)

    Mantilla, Andres Eduardo

    Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization, yet usually they have the largest impact on reserves and production forecasts, and consequently on the economy of a project. The difficulty of estimating them comes from the fact that porosity and permeability may vary significantly over the reservoir volume, but can only be sampled at well locations, often using different technologies at different scales of observation. An accurate estimation of the spatial distribution of porosity and permeability is of key importance, because it translates into higher success rates in infill drilling, and fewer wells required for draining the reservoir. The purpose of this thesis is to enhance the characterization of subsurface reservoirs by improving the prediction of petrophysical properties through the combination of reservoir geophysics and reservoir engineering observations and models. To fulfill this goal, I take advantage of the influence that petrophysical properties have on seismic and production data, and formulate, implement, and demonstrate the applicability of an inversion approach that integrates seismic and production-related observations with a-priori information about porosity and permeability. Being constrained by physical models and observations, the resulting estimates are appropriate for making reservoir management decisions. I use synthetic models to test the proposed inversion approach. Results from these tests show that, because of the excellent spatial coverage of seismic data, incorporating seismic-derived attributes related to petrophysical properties can significantly improve the estimates of porosity and permeability. The results also highlight the importance of using a-priori information about the relationship between porosity and permeability. The last chapters of this thesis describe a practical application of the proposed joint inversion approach. This application includes a rock

  3. Integrated petrophysical and reservoir characterization workflow to enhance permeability and water saturation prediction

    Science.gov (United States)

    Al-Amri, Meshal; Mahmoud, Mohamed; Elkatatny, Salaheldin; Al-Yousef, Hasan; Al-Ghamdi, Tariq

    2017-07-01

    Accurate estimation of permeability is essential in reservoir characterization and in determining fluid flow in porous media which greatly assists optimize the production of a field. Some of the permeability prediction techniques such as Porosity-Permeability transforms and recently artificial intelligence and neural networks are encouraging but still show moderate to good match to core data. This could be due to limitation to homogenous media while the knowledge about geology and heterogeneity is indirectly related or absent. The use of geological information from core description as in Lithofacies which includes digenetic information show a link to permeability when categorized into rock types exposed to similar depositional environment. The objective of this paper is to develop a robust combined workflow integrating geology and petrophysics and wireline logs in an extremely heterogeneous carbonate reservoir to accurately predict permeability. Permeability prediction is carried out using pattern recognition algorithm called multi-resolution graph-based clustering (MRGC). We will bench mark the prediction results with hard data from core and well test analysis. As a result, we showed how much better improvements are achieved in the permeability prediction when geology is integrated within the analysis. Finally, we use the predicted permeability as an input parameter in J-function and correct for uncertainties in saturation calculation produced by wireline logs using the classical Archie equation. Eventually, high level of confidence in hydrocarbon volumes estimation is reached when robust permeability and saturation height functions are estimated in presence of important geological details that are petrophysically meaningful.

  4. Pressure and fluid saturation prediction in a multicomponent reservoir, using combined seismic and electromagnetic imaging

    International Nuclear Information System (INIS)

    Hoversten, G.M.; Gritto, Roland; Washbourne, John; Daley, Tom

    2002-01-01

    This paper presents a method for combining seismic and electromagnetic measurements to predict changes in water saturation, pressure, and CO 2 gas/oil ratio in a reservoir undergoing CO 2 flood. Crosswell seismic and electromagnetic data sets taken before and during CO 2 flooding of an oil reservoir are inverted to produce crosswell images of the change in compressional velocity, shear velocity, and electrical conductivity during a CO 2 injection pilot study. A rock properties model is developed using measured log porosity, fluid saturations, pressure, temperature, bulk density, sonic velocity, and electrical conductivity. The parameters of the rock properties model are found by an L1-norm simplex minimization of predicted and observed differences in compressional velocity and density. A separate minimization, using Archie's law, provides parameters for modeling the relations between water saturation, porosity, and the electrical conductivity. The rock-properties model is used to generate relationships between changes in geophysical parameters and changes in reservoir parameters. Electrical conductivity changes are directly mapped to changes in water saturation; estimated changes in water saturation are used along with the observed changes in shear wave velocity to predict changes in reservoir pressure. The estimation of the spatial extent and amount of CO 2 relies on first removing the effects of the water saturation and pressure changes from the observed compressional velocity changes, producing a residual compressional velocity change. This velocity change is then interpreted in terms of increases in the CO 2 /oil ratio. Resulting images of the CO 2 /oil ratio show CO 2 -rich zones that are well correlated to the location of injection perforations, with the size of these zones also correlating to the amount of injected CO 2 . The images produced by this process are better correlated to the location and amount of injected CO 2 than are any of the individual

  5. The Controls of Pore-Throat Structure on Fluid Performance in Tight Clastic Rock Reservoir: A Case from the Upper Triassic of Chang 7 Member, Ordos Basin, China

    Directory of Open Access Journals (Sweden)

    Yunlong Zhang

    2018-01-01

    Full Text Available The characteristics of porosity and permeability in tight clastic rock reservoir have significant difference from those in conventional reservoir. The increased exploitation of tight gas and oil requests further understanding of fluid performance in the nanoscale pore-throat network of the tight reservoir. Typical tight sandstone and siltstone samples from Ordos Basin were investigated, and rate-controlled mercury injection capillary pressure (RMICP and nuclear magnetic resonance (NMR were employed in this paper, combined with helium porosity and air permeability data, to analyze the impact of pore-throat structure on the storage and seepage capacity of these tight oil reservoirs, revealing the control factors of economic petroleum production. The researches indicate that, in the tight clastic rock reservoir, largest throat is the key control on the permeability and potentially dominates the movable water saturation in the reservoir. The storage capacity of the reservoir consists of effective throat and pore space. Although it has a relatively steady and significant proportion that resulted from the throats, its variation is still dominated by the effective pores. A combination parameter (ε that was established to be as an integrated characteristic of pore-throat structure shows effectively prediction of physical capability for hydrocarbon resource of the tight clastic rock reservoir.

  6. Integrated Reservoir Modeling of CO2-EOR Performance and Storage Potential in the Farnsworth Field Unit, Texas.

    Science.gov (United States)

    Ampomah, W.; Balch, R. S.; Cather, M.; Dai, Z.

    2017-12-01

    We present a performance assessment methodology and storage potential for CO2 enhanced oil recovery (EOR) in partially depleted reservoirs. A three dimensional heterogeneous reservoir model was developed based on geological, geophysics and engineering data from Farnsworth field Unit (FWU). The model aided in improved characterization of prominent rock properties within the Pennsylvanian aged Morrow sandstone reservoir. Seismic attributes illuminated previously unknown faults and structural elements within the field. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). Datasets including net-to-gross ratio, volume of shale, permeability, and burial history were used to model initial fault transmissibility based on Sperivick model. An improved history match of primary and secondary recovery was performed to set the basis for a CO2 flood study. The performance of the current CO2 miscible flood patterns was subsequently calibrated to historical production and injection data. Several prediction models were constructed to study the effect of recycling, addition of wells and /or new patterns, water alternating gas (WAG) cycles and optimum amount of CO2 purchase on incremental oil production and CO2 storage in the FWU. The history matching study successfully validated the presence of the previously undetected faults within FWU that were seen in the seismic survey. The analysis of the various prediction scenarios showed that recycling a high percentage of produced gas, addition of new wells and a gradual reduction in CO2 purchase after several years of operation would be the best approach to ensure a high percentage of recoverable incremental oil and sequestration of anthropogenic CO2 within the Morrow reservoir. Larger percentage of stored CO2 were dissolved in residual oil and less amount existed as supercritical free CO2. The geomechanical analysis on the caprock proved to an

  7. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  8. Performance modeling of an integral, self-regulating cesium reservoir for the ATI-TFE

    International Nuclear Information System (INIS)

    Thayer, K.L.; Ramalingam, M.L.; Young, T.J.

    1993-01-01

    This work covers the performance modeling of an integral metal-matrix cesium-graphite reservoir for operation in the Advanced Thermionic Initiative-Thermionic Fuel Element (ATI-TFE) converter configuration. The objectives of this task were to incorporate an intercalated cesium-graphite reservoir for the 3C 24 Cs→2C 36 Cs+Cs (g) two phase equilibrium reaction into the emitter lead region of the ATI-TFE. A semi two-dimensional, cylindrical TFE computer model was used to obtain thermal and electrical converter output characteristics for various reservoir locations. The results of this study are distributions for the interelectrode voltage, output current density, and output power density as a function of axial position along the TFE emitter. This analysis was accomplished by identifying an optimum cesium pressure for three representative pins in the ATI ''driverless'' reactor core and determining the corresponding position of the graphite reservoir in the ATI-TFE lead region. The position for placement of the graphite reservoir was determined by performing a first-order heat transfer analysis of the TFE lead region to determine its temperature distribution. The results of this analysis indicate that for the graphite reservoirs investigated the 3C 24 Cs→2C 36 Cs+Cs (g) equilibrium reaction reservoir is ideal for placement in the TFE emitter lead region. This reservoir can be directly coupled to the emitter, through conduction, to provide the desired cesium pressure for optimum performance. The cesium pressure corresponding to the optimum converter output performance was found to be 2.18 torr for the ATI core least power TFE, 2.92 torr for the average power TFE, and 4.93 torr for the maximum power TFE

  9. Prediction of calcite Cement Distribution in Shallow Marine Sandstone Reservoirs using Seismic Data

    Energy Technology Data Exchange (ETDEWEB)

    Bakke, N.E.

    1996-12-31

    This doctoral thesis investigates how calcite cemented layers can be detected by reflection seismic data and how seismic data combined with other methods can be used to predict lateral variation in calcite cementation in shallow marine sandstone reservoirs. Focus is on the geophysical aspects. Sequence stratigraphy and stochastic modelling aspects are only covered superficially. Possible sources of calcite in shallow marine sandstone are grouped into internal and external sources depending on their location relative to the presently cemented rock. Well data and seismic data from the Troll Field in the Norwegian North Sea have been analysed. Tuning amplitudes from stacks of thin calcite cemented layers are analysed. Tuning effects are constructive or destructive interference of pulses resulting from two or more closely spaced reflectors. The zero-offset tuning amplitude is shown to depend on calcite content in the stack and vertical stack size. The relationship is found by regression analysis based on extensive seismic modelling. The results are used to predict calcite distribution in a synthetic and a real data example. It is found that describing calcite cemented beds in shallow marine sandstone reservoirs is not a deterministic problem. Hence seismic inversion and sequence stratigraphy interpretation of well data have been combined in a probabilistic approach to produce models of calcite cemented barriers constrained by a maximum amount of information. It is concluded that seismic data can provide valuable information on distribution of calcite cemented beds in reservoirs where the background sandstones are relatively homogeneous. 63 refs., 78 figs., 10 tabs.

  10. Prediction of radionuclide accumulation in main ecosystem components of NPP cooling water reservoirs and assessment of acceptable radionuclide disposal into water reservoir

    International Nuclear Information System (INIS)

    Egorov, Yu.A.; Kazakov, S.V.

    1987-01-01

    The problems of prediction of radionuclide accumulation in ecosystem main components of NPP cooling water-reservoirs (CWR) and assessment of radionuclide acceptable disposal into water reservoir are considered. Two models are nessecary for the calculation technique: model of radionuclide migration and accumulation in CWR ecosystem components and calculation model of population dose commitment due to water consumption (at the public health approach to the normalization of the NPP radioactive effect on CWC) or calculation model of dose commitment on hydrocenosis components (at the ecological approach to the normalization). Analytical calculations and numerical calculation results in the model CWC, located in the USSR middle region, are presented

  11. Investigating the expected long-term production performance of shale reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Vassilellis, G.D.; Li, C.; Seager, R.J.H. [Gaffney, Cline and Associates, Houston, TX (United States); Moos, D. [Geomechanics International, Houston, TX (United States)

    2010-07-01

    Although there is global interest in developing shale plays, the traditional volumetric and material balance approaches that are used for petroleum asset evaluation do not address the special attributes of such formations. The performance of a particular deposit is currently determined by analyzing historical records statistically in developed areas and applying the derived type curves in new areas by assuming performance similarity. The assumption of similarity is challenged by the wealth of parameters influencing performance, which tend to differ, introducing considerable uncertainties into predictions. Historical records support only the early production history, while late performance is extrapolated without many reference points to match. This paper presented an investigation of the applicability of traditional and non-traditional empirical, analytical and numerical methods that are used to predict shale well performance. The purpose of the study was to rationalize the link between natural/stimulated rock description with oil and gas recovery mechanisms in a manner that is practical at different scales of resolution and covers early and late times. The paper discussed the use of special features such as flow through fracture networks, gas desorption and geomechanical effects that are incorporated in numerical simulation in a way that relates to the measurable petrophysical and geophysical input. The paper described the shale engineering concept and provided a description of the model. The Eagle Ford shale was presented as a case study. It was concluded that a reservoir simulation model with pseudo-lateral connections could describe the flow behaviour of a typical shale well, and could match shale gas well performance even if limited information was available. 20 refs., 9 figs.

  12. Reservoir computer predictions for the Three Meter magnetic field time evolution

    Science.gov (United States)

    Perevalov, A.; Rojas, R.; Lathrop, D. P.; Shani, I.; Hunt, B. R.

    2017-12-01

    The source of the Earth's magnetic field is the turbulent flow of liquid metal in the outer core. Our experiment's goal is to create Earth-like dynamo, to explore the mechanisms and to understand the dynamics of the magnetic and velocity fields. Since it is a complicated system, predictions of the magnetic field is a challenging problem. We present results of mimicking the three Meter experiment by a reservoir computer deep learning algorithm. The experiment is a three-meter diameter outer sphere and a one-meter diameter inner sphere with the gap filled with liquid sodium. The spheres can rotate up to 4 and 14 Hz respectively, giving a Reynolds number near to 108. Two external electromagnets apply magnetic fields, while an array of 31 external and 2 internal Hall sensors measure the resulting induced fields. We use this magnetic probe data to train a reservoir computer to predict the 3M time evolution and mimic waves in the experiment. Surprisingly accurate predictions can be made for several magnetic dipole time scales. This shows that such a complicated MHD system's behavior can be predicted. We gratefully acknowledge support from NSF EAR-1417148.

  13. Water Pollution Prediction in the Three Gorges Reservoir Area and Countermeasures for Sustainable Development of the Water Environment

    Directory of Open Access Journals (Sweden)

    Yinghui Li

    2017-10-01

    Full Text Available The Three Gorges Project was implemented in 1994 to promote sustainable water resource use and development of the water environment in the Three Gorges Reservoir Area (hereafter “Reservoir Area”. However, massive discharge of wastewater along the river threatens these goals; therefore, this study employs a grey prediction model (GM to predict the annual emissions of primary pollution sources, including industrial wastewater, domestic wastewater, and oily and domestic wastewater from ships, that influence the Three Gorges Reservoir Area water environment. First, we optimize the initial values of a traditional GM (1,1 model, and build a new GM (1,1 model that minimizes the sum of squares of the relative simulation errors. Second, we use the new GM (1,1 model to simulate historical annual emissions data for the four pollution sources and thereby test the effectiveness of the model. Third, we predict the annual emissions of the four pollution sources in the Three Gorges Reservoir Area for a future period. The prediction results reveal the annual emission trends for the major wastewater types, and indicate the primary sources of water pollution in the Three Gorges Reservoir Area. Based on our predictions, we suggest several countermeasures against water pollution and towards the sustainable development of the water environment in the Three Gorges Reservoir Area.

  14. Water Pollution Prediction in the Three Gorges Reservoir Area and Countermeasures for Sustainable Development of the Water Environment

    Science.gov (United States)

    Huang, Shuaijin; Qu, Xuexin

    2017-01-01

    The Three Gorges Project was implemented in 1994 to promote sustainable water resource use and development of the water environment in the Three Gorges Reservoir Area (hereafter “Reservoir Area”). However, massive discharge of wastewater along the river threatens these goals; therefore, this study employs a grey prediction model (GM) to predict the annual emissions of primary pollution sources, including industrial wastewater, domestic wastewater, and oily and domestic wastewater from ships, that influence the Three Gorges Reservoir Area water environment. First, we optimize the initial values of a traditional GM (1,1) model, and build a new GM (1,1) model that minimizes the sum of squares of the relative simulation errors. Second, we use the new GM (1,1) model to simulate historical annual emissions data for the four pollution sources and thereby test the effectiveness of the model. Third, we predict the annual emissions of the four pollution sources in the Three Gorges Reservoir Area for a future period. The prediction results reveal the annual emission trends for the major wastewater types, and indicate the primary sources of water pollution in the Three Gorges Reservoir Area. Based on our predictions, we suggest several countermeasures against water pollution and towards the sustainable development of the water environment in the Three Gorges Reservoir Area. PMID:29077006

  15. Water Pollution Prediction in the Three Gorges Reservoir Area and Countermeasures for Sustainable Development of the Water Environment.

    Science.gov (United States)

    Li, Yinghui; Huang, Shuaijin; Qu, Xuexin

    2017-10-27

    The Three Gorges Project was implemented in 1994 to promote sustainable water resource use and development of the water environment in the Three Gorges Reservoir Area (hereafter "Reservoir Area"). However, massive discharge of wastewater along the river threatens these goals; therefore, this study employs a grey prediction model (GM) to predict the annual emissions of primary pollution sources, including industrial wastewater, domestic wastewater, and oily and domestic wastewater from ships, that influence the Three Gorges Reservoir Area water environment. First, we optimize the initial values of a traditional GM (1,1) model, and build a new GM (1,1) model that minimizes the sum of squares of the relative simulation errors. Second, we use the new GM (1,1) model to simulate historical annual emissions data for the four pollution sources and thereby test the effectiveness of the model. Third, we predict the annual emissions of the four pollution sources in the Three Gorges Reservoir Area for a future period. The prediction results reveal the annual emission trends for the major wastewater types, and indicate the primary sources of water pollution in the Three Gorges Reservoir Area. Based on our predictions, we suggest several countermeasures against water pollution and towards the sustainable development of the water environment in the Three Gorges Reservoir Area.

  16. Integrating sequence stratigraphy and rock-physics to interpret seismic amplitudes and predict reservoir quality

    Science.gov (United States)

    Dutta, Tanima

    This dissertation focuses on the link between seismic amplitudes and reservoir properties. Prediction of reservoir properties, such as sorting, sand/shale ratio, and cement-volume from seismic amplitudes improves by integrating knowledge from multiple disciplines. The key contribution of this dissertation is to improve the prediction of reservoir properties by integrating sequence stratigraphy and rock physics. Sequence stratigraphy has been successfully used for qualitative interpretation of seismic amplitudes to predict reservoir properties. Rock physics modeling allows quantitative interpretation of seismic amplitudes. However, often there is uncertainty about selecting geologically appropriate rock physics model and its input parameters, away from the wells. In the present dissertation, we exploit the predictive power of sequence stratigraphy to extract the spatial trends of sedimentological parameters that control seismic amplitudes. These spatial trends of sedimentological parameters can serve as valuable constraints in rock physics modeling, especially away from the wells. Consequently, rock physics modeling, integrated with the trends from sequence stratigraphy, become useful for interpreting observed seismic amplitudes away from the wells in terms of underlying sedimentological parameters. We illustrate this methodology using a comprehensive dataset from channelized turbidite systems, deposited in minibasin settings in the offshore Equatorial Guinea, West Africa. First, we present a practical recipe for using closed-form expressions of effective medium models to predict seismic velocities in unconsolidated sandstones. We use an effective medium model that combines perfectly rough and smooth grains (the extended Walton model), and use that model to derive coordination number, porosity, and pressure relations for P and S wave velocities from experimental data. Our recipe provides reasonable fits to other experimental and borehole data, and specifically

  17. Fuzzy logic prediction of dew point pressure of selected Iranian gas condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Nowroozi, Saeed [Shahid Bahonar Univ. of Kerman (Iran); Iranian Offshore Oil Company (I.O.O.C.) (Iran); Ranjbar, Mohammad; Hashemipour, Hassan; Schaffie, Mahin [Shahid Bahonar Univ. of Kerman (Iran)

    2009-12-15

    The experimental determination of dew point pressure in a window PVT cell is often difficult especially in the case of lean retrograde gas condensate. Besides all statistical, graphical and experimental methods, the fuzzy logic method can be useful and more reliable for estimation of reservoir properties. Fuzzy logic can overcome uncertainty existent in many reservoir properties. Complexity, non-linearity and vagueness are some reservoir parameter characteristics, which can be propagated simply by fuzzy logic. The fuzzy logic dew point pressure modeling system used in this study is a multi input single output (MISO) Mamdani system. The model was developed using experimentally constant volume depletion (CVD) measured samples of some Iranian fields. The performance of the model is compared against the performance of some of the most accurate and general correlations for dew point pressure calculation. Results show that this novel method is more accurate and reliable with an average absolute deviation of 1.33% and 2.68% for developing and checking, respectively. (orig.)

  18. Physical Aspects in Upscaling of Fractured Reservoirs and Improved Oil Recovery Prediction

    NARCIS (Netherlands)

    Salimi, H.

    2010-01-01

    This thesis is concerned with upscaled models for waterflooded naturally fractured reservoirs (NFRs). Naturally fractured petroleum reservoirs provide over 20% of the world’s oil reserves and production. From the fluid-flow point of view, a fractured reservoir is defined as a reservoir in which a

  19. Using Thermodynamics to Predict the Outcomes of Nitrate-Based Oil Reservoir Souring Control Interventions

    Directory of Open Access Journals (Sweden)

    Jan Dolfing

    2017-12-01

    Full Text Available Souring is the undesirable production of hydrogen sulfide (H2S in oil reservoirs by sulfate-reducing bacteria (SRB. Souring is a common problem during secondary oil recovery via water flooding, especially when seawater with its high sulfate concentration is introduced. Nitrate injection into these oil reservoirs can prevent and remediate souring by stimulating nitrate-reducing bacteria (NRB. Two conceptually different mechanisms for NRB-facilitated souring control have been proposed: nitrate-sulfate competition for electron donors (oil-derived organics or H2 and nitrate driven sulfide oxidation. Thermodynamics can facilitate predictions about which nitrate-driven mechanism is most likely to occur in different scenarios. From a thermodynamic perspective the question “Which reaction yields more energy, nitrate driven oxidation of sulfide or nitrate driven oxidation of organic compounds?” can be rephrased as: “Is acetate driven sulfate reduction to sulfide exergonic or endergonic?” Our analysis indicates that under conditions encountered in oil fields, sulfate driven oxidation of acetate (or other SRB organic electron donors is always more favorable than sulfide oxidation to sulfate. That predicts that organotrophic NRB that oxidize acetate would outcompete lithotrophic NRB that oxidize sulfide. However, sulfide oxidation to elemental sulfur is different. At low acetate HS− oxidation is more favorable than acetate oxidation. Incomplete oxidation of sulfide to S0 is likely to occur when nitrate levels are low, and is favored by low temperatures; conditions that can be encountered at oil field above-ground facilities where intermediate sulfur compounds like S0 may cause corrosion. These findings have implications for reservoir management strategies and for assessing the success and progress of nitrate-based souring control strategies and the attendant risks of corrosion associated with souring and nitrate injection.

  20. Exploitation and Optimization of Reservoir Performance in Hunton Formation, Oklahoma

    Energy Technology Data Exchange (ETDEWEB)

    Mohan Kelkar

    2007-06-30

    Hunton formation in Oklahoma has been the subject of attention for the last ten years. The new interest started with the drilling of the West Carney field in 1995 in Lincoln County. Subsequently, many other operators have expanded the search for oil and gas in Hunton formation in other parts of Oklahoma. These fields exhibit many unique production characteristics, including: (1) decreasing water-oil or water-gas ratio over time; (2) decreasing gas-oil ratio followed by an increase; (3) poor prediction capability of the reserves based on the log data; and (4) low geological connectivity but high hydrodynamic connectivity. The purpose of this investigation is to understand the principal mechanisms affecting the production, and propose methods by which we can optimize the production from fields with similar characteristics.

  1. Predicting cyanobacterial abundance, microcystin, and geosmin in a eutrophic drinking-water reservoir using a 14-year dataset

    Science.gov (United States)

    Harris, Ted D.; Graham, Jennifer L.

    2017-01-01

    Cyanobacterial blooms degrade water quality in drinking water supply reservoirs by producing toxic and taste-and-odor causing secondary metabolites, which ultimately cause public health concerns and lead to increased treatment costs for water utilities. There have been numerous attempts to create models that predict cyanobacteria and their secondary metabolites, most using linear models; however, linear models are limited by assumptions about the data and have had limited success as predictive tools. Thus, lake and reservoir managers need improved modeling techniques that can accurately predict large bloom events that have the highest impact on recreational activities and drinking-water treatment processes. In this study, we compared 12 unique linear and nonlinear regression modeling techniques to predict cyanobacterial abundance and the cyanobacterial secondary metabolites microcystin and geosmin using 14 years of physiochemical water quality data collected from Cheney Reservoir, Kansas. Support vector machine (SVM), random forest (RF), boosted tree (BT), and Cubist modeling techniques were the most predictive of the compared modeling approaches. SVM, RF, and BT modeling techniques were able to successfully predict cyanobacterial abundance, microcystin, and geosmin concentrations <60,000 cells/mL, 2.5 µg/L, and 20 ng/L, respectively. Only Cubist modeling predicted maxima concentrations of cyanobacteria and geosmin; no modeling technique was able to predict maxima microcystin concentrations. Because maxima concentrations are a primary concern for lake and reservoir managers, Cubist modeling may help predict the largest and most noxious concentrations of cyanobacteria and their secondary metabolites.

  2. Prediction of abrupt reservoir compaction and surface subsidence due to pore collapse in carbonates

    Energy Technology Data Exchange (ETDEWEB)

    Smits, R.M.M.; de Waal, A.; van Kooten, J.F.C.

    1986-01-01

    A new procedure has been developed to predict the abrupt in-situ compaction and the associated surface subsidence above high-porosity carbonate fields showing pore collapse. The approach is based on an extensive laboratory compaction study in which the effects of carbonate type, porosity, core preparation, pore saturant, horizontal to vertical stress ratio and loading rate on the pore collapse behaviour were investigated. For each carbonate type a trendline was established describing the relationship between the porosity after collapse and the vertical effective stress. This trendline concept, in combination with existing subsidence models, enables reservoir compaction and surface subsidence to be predicted on the basis of wireline porosity logs. Static and dynamic elastic constants were found to be uncorrelated during pore collapse. The position of the trendline depends strongly on carbonate type, pore saturant, loading rate and stress ratio. Therefore procedures are given to derive the correct in-situ trendline from laboratory compaction experiments.

  3. Prediction of abrupt reservoir compaction and surface subsidence caused by pore collapse in carbonates

    Energy Technology Data Exchange (ETDEWEB)

    Smits, R.M.M.; De Waal, J.A.; Van Kootan, J.F.C.

    1988-06-01

    A new procedure has been developed to predict the abrupt in-situ compaction and the associated surface subsidence above high-porosity carbonate fields that show pore collapse. The approach is based on an extensive laboratory compaction study in which the effects of carbonate type, porosity, core preparation, pore saturant, horizontal/vertical stress ratio, and loading rate on pore-collapse behavior were investigated. For a number of carbonate types, a trendline was established that describes the relationship between the porosity after collapse and the vertical effective stress. This trendline concept, in combination with existing subsidence models, enables reservoir compaction and surface subsidence to be predicted on the basis of wireline porosity logs. Static and dynamic elastic constants were found to be uncorrelated during pore collapse. The position of the trendline depends strongly on carbonate type, pore saturant, loading rate, and stress ratio. Therefore, procedures are given to derive the correct in-situ trendline from laboratory compaction experiments.

  4. The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA.

    Science.gov (United States)

    Cho, Kyung Hwa; Pachepsky, Yakov A; Kim, Joon Ha; Kim, Jung-Woo; Park, Mi-Hyun

    2012-10-01

    This study assessed fecal coliform contamination in the Wachusett Reservoir Watershed in Massachusetts, USA using Soil and Water Assessment Tool (SWAT) because bacteria are one of the major water quality parameters of concern. The bacteria subroutine in SWAT, considering in-stream bacteria die-off only, was modified in this study to include solar radiation-associated die-off and the contribution of wildlife. The result of sensitivity analysis demonstrates that solar radiation is one of the most significant fate factors of fecal coliform. A water temperature-associated function to represent the contribution of beaver activity in the watershed to fecal contamination improved prediction accuracy. The modified SWAT model provides an improved estimate of bacteria from the watershed. Our approach will be useful for simulating bacterial concentrations to provide predictive and reliable information of fecal contamination thus facilitating the implementation of effective watershed management. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. APPLICATION OF INTEGRATED RESERVOIR MANAGEMENT AND RESERVOIR CHARACTERIZATION

    Energy Technology Data Exchange (ETDEWEB)

    Jack Bergeron; Tom Blasingame; Louis Doublet; Mohan Kelkar; George Freeman; Jeff Callard; David Moore; David Davies; Richard Vessell; Brian Pregger; Bill Dixon; Bryce Bezant

    2000-03-01

    Reservoir performance and characterization are vital parameters during the development phase of a project. Infill drilling of wells on a uniform spacing, without regard to characterization does not optimize development because it fails to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, especially carbonate reservoirs. These reservoirs are typically characterized by: (1) large, discontinuous pay intervals; (2) vertical and lateral changes in reservoir properties; (3) low reservoir energy; (4) high residual oil saturation; and (5) low recovery efficiency. The operational problems they encounter in these types of reservoirs include: (1) poor or inadequate completions and stimulations; (2) early water breakthrough; (3) poor reservoir sweep efficiency in contacting oil throughout the reservoir as well as in the nearby well regions; (4) channeling of injected fluids due to preferential fracturing caused by excessive injection rates; and (5) limited data availability and poor data quality. Infill drilling operations only need target areas of the reservoir which will be economically successful. If the most productive areas of a reservoir can be accurately identified by combining the results of geological, petrophysical, reservoir performance, and pressure transient analyses, then this ''integrated'' approach can be used to optimize reservoir performance during secondary and tertiary recovery operations without resorting to ''blanket'' infill drilling methods. New and emerging technologies such as geostatistical modeling, rock typing, and rigorous decline type curve analysis can be used to quantify reservoir quality and the degree of interwell communication. These results can then be used to develop a 3-D simulation model for prediction of infill locations. The application of reservoir surveillance techniques to identify additional reservoir ''pay'' zones

  6. Application of sequence stratigraphy to carbonate reservoir prediction, Early Palaeozoic eastern Warburton basin, South Australia

    Energy Technology Data Exchange (ETDEWEB)

    Xiaowen S.; Stuart, W.J.

    1996-12-31

    The Early Palaeozoic Warburton Basin underlies the gas and oil producing Cooper and Eromanga Basins. Postdepositional tectonism created high potential fracture porosities, complicating the stratigraphy and making reservoir prediction difficult. Sequence stratigraphy integrating core, cuttings, well-log, seismic and biostratigraphic data has recognized a carbonate-dominated to mixed carbonate/siliciclastic supersequence comprising several depositional sequences. Biostratigraphy based on trilobites and conodonts ensures reliable well and seismic correlations across structurally complex areas. Lithofacies interpretation indicates sedimentary environments ranging from carbonate inner shelf, peritidal, shelf edge, deep outer shelf and slope to basin. Log facies show gradually upward shallowing trends or abrupt changes indicating possible sequence boundaries. With essential depositional models and sequence analysis from well data, seismic facies suggest general reflection configurations including parallel-continuous layered patterns indicating uniform neuritic shelf, and mounded structures suggesting carbonate build-ups and pre-existing volcanic relief. Seismic stratigraphy also reveals inclined slope and onlapping margins of a possibly isolated platform geometry. The potential reservoirs are dolomitized carbonates containing oomoldic, vuggy, intercrystalline and fracture porosities in lowstand systems tracts either on carbonate mounds and shelf crests or below shelf edge. The source rock is a deep basinal argillaceous mudstone, and the seal is fine-grained siltstone/shale of the transgressive system tract.

  7. Application of sequence stratigraphy to carbonate reservoir prediction, Early Palaeozoic eastern Warburton basin, South Australia

    Energy Technology Data Exchange (ETDEWEB)

    Xiaowen S.; Stuart, W.J.

    1996-01-01

    The Early Palaeozoic Warburton Basin underlies the gas and oil producing Cooper and Eromanga Basins. Postdepositional tectonism created high potential fracture porosities, complicating the stratigraphy and making reservoir prediction difficult. Sequence stratigraphy integrating core, cuttings, well-log, seismic and biostratigraphic data has recognized a carbonate-dominated to mixed carbonate/siliciclastic supersequence comprising several depositional sequences. Biostratigraphy based on trilobites and conodonts ensures reliable well and seismic correlations across structurally complex areas. Lithofacies interpretation indicates sedimentary environments ranging from carbonate inner shelf, peritidal, shelf edge, deep outer shelf and slope to basin. Log facies show gradually upward shallowing trends or abrupt changes indicating possible sequence boundaries. With essential depositional models and sequence analysis from well data, seismic facies suggest general reflection configurations including parallel-continuous layered patterns indicating uniform neuritic shelf, and mounded structures suggesting carbonate build-ups and pre-existing volcanic relief. Seismic stratigraphy also reveals inclined slope and onlapping margins of a possibly isolated platform geometry. The potential reservoirs are dolomitized carbonates containing oomoldic, vuggy, intercrystalline and fracture porosities in lowstand systems tracts either on carbonate mounds and shelf crests or below shelf edge. The source rock is a deep basinal argillaceous mudstone, and the seal is fine-grained siltstone/shale of the transgressive system tract.

  8. Well and Inflow Performance Relationship for Heavy Oil Reservoir under Heating Treatment

    KAUST Repository

    Hakiki, Farizal

    2017-10-17

    Well and Inflow Performance Relationship, termed TPR and IPR, respectively have been the unfailing methods to predict well performance. It is further to determine the schemes on optimising production. The main intention of the study is to explore TPR and IPR under heating treatment for heavy oil well. Klamono is a mature field which mostly has depleted wells, it produces heavy oil within 18.5 °API (>0.95 g/cc oil density), and therefore, artificial lifting method is necessary. Sucker Road Pump (SRP) and Electrical Submersible Pump (ESP) are the most deployed artificial lifting method in this reservoir. To boost the heavy oil production, the application of Electric Downhole Heater (EDH) in Well KLO-X1 is being studied. Whole Klamono\\'s production is more than 100,000 blpd within 97-99% water cut. By installing EDH, oil viscosity is decreased hence oil mobility ratio will play a role to decrease water cut. EDH is installed together with the tubing joint to simplify its application in the wellbore. The study shows that EDH application can elevate fluid (mixed oil and brine) temperature. Oil viscosity confirms a reduction from 68 to 46 cP. The gross well production is up to 12.2 bopd due optimising its outflow performance and reducing 97.5 to 96.9% water cut. The field data gives an incremental of 4.9 bopd. The computational results only show an attainment of net oil production up to 8.3 bopd (2 bopd incremental). The EDH works to lessen both density and viscosity as we hypothesised for the mechanism of thermally induced oil production improvement. The evaluation study on its economics aspect exhibits good result that is 1.4 USD/bbl additional profit margin according to field data despite the challenging annual rig rent cost. Following the field data, the expected net income through analytical model revealed that this project is financially promising.

  9. Well and Inflow Performance Relationship for Heavy Oil Reservoir under Heating Treatment

    KAUST Repository

    Hakiki, Farizal; Aditya, A.; Ulitha, D. T.; Shidqi, M.; Adi, W. S.; Wibowo, K. H.; Barus, M.

    2017-01-01

    Well and Inflow Performance Relationship, termed TPR and IPR, respectively have been the unfailing methods to predict well performance. It is further to determine the schemes on optimising production. The main intention of the study is to explore TPR and IPR under heating treatment for heavy oil well. Klamono is a mature field which mostly has depleted wells, it produces heavy oil within 18.5 °API (>0.95 g/cc oil density), and therefore, artificial lifting method is necessary. Sucker Road Pump (SRP) and Electrical Submersible Pump (ESP) are the most deployed artificial lifting method in this reservoir. To boost the heavy oil production, the application of Electric Downhole Heater (EDH) in Well KLO-X1 is being studied. Whole Klamono's production is more than 100,000 blpd within 97-99% water cut. By installing EDH, oil viscosity is decreased hence oil mobility ratio will play a role to decrease water cut. EDH is installed together with the tubing joint to simplify its application in the wellbore. The study shows that EDH application can elevate fluid (mixed oil and brine) temperature. Oil viscosity confirms a reduction from 68 to 46 cP. The gross well production is up to 12.2 bopd due optimising its outflow performance and reducing 97.5 to 96.9% water cut. The field data gives an incremental of 4.9 bopd. The computational results only show an attainment of net oil production up to 8.3 bopd (2 bopd incremental). The EDH works to lessen both density and viscosity as we hypothesised for the mechanism of thermally induced oil production improvement. The evaluation study on its economics aspect exhibits good result that is 1.4 USD/bbl additional profit margin according to field data despite the challenging annual rig rent cost. Following the field data, the expected net income through analytical model revealed that this project is financially promising.

  10. Predicting interwell heterogeneity in fluvial-deltaic reservoirs: Outcrop observations and applications of progressive facies variation through a depositional cycle

    Energy Technology Data Exchange (ETDEWEB)

    Knox, P.R.; Barton, M.D. [Univ. of Texas, Austin, TX (United States)

    1997-08-01

    Nearly 11 billion barrels of mobile oil remain in known domestic fluvial-deltaic reservoirs despite their mature status. A large percentage of this strategic resource is in danger of permanent loss through premature abandonment. Detailed reservoir characterization studies that integrate advanced technologies in geology, geophysics, and engineering are needed to identify remaining resources that can be targeted by near-term recovery methods, resulting in increased production and the postponement of abandonment. The first and most critical step of advanced characterization studies is the identification of reservoir architecture. However, existing subsurface information, primarily well logs, provides insufficient lateral resolution to identify low-permeability boundaries that exist between wells and compartmentalize the reservoir. Methods to predict lateral variability in fluvial-deltaic reservoirs have been developed on the basis of outcrop studies and incorporate identification of depositional setting and position within a depositional cycle. The position of a reservoir within the framework of a depositional cycle is critical. Outcrop studies of the Cretaceous Ferron Sandstone of Utah have demonstrated that the architecture and internal heterogeneity of sandstones deposited within a given depositional setting (for example, delta front) vary greatly depending upon whether they were deposited in the early, progradational part of a cycle or the late, retrogradational part of a cycle. The application of techniques similar to those used by this study in other fluvial-deltaic reservoirs will help to estimate the amount and style of remaining potential in mature reservoirs through a quicklook evaluation, allowing operators to focus characterization efforts on reservoirs that have the greatest potential to yield additional resources.

  11. Predicting Formation Damage in Aquifer Thermal Energy Storage Systems Utilizing a Coupled Hydraulic-Thermal-Chemical Reservoir Model

    Science.gov (United States)

    Müller, Daniel; Regenspurg, Simona; Milsch, Harald; Blöcher, Guido; Kranz, Stefan; Saadat, Ali

    2014-05-01

    In aquifer thermal energy storage (ATES) systems, large amounts of energy can be stored by injecting hot water into deep or intermediate aquifers. In a seasonal production-injection cycle, water is circulated through a system comprising the porous aquifer, a production well, a heat exchanger and an injection well. This process involves large temperature and pressure differences, which shift chemical equilibria and introduce or amplify mechanical processes. Rock-fluid interaction such as dissolution and precipitation or migration and deposition of fine particles will affect the hydraulic properties of the porous medium and may lead to irreversible formation damage. In consequence, these processes determine the long-term performance of the ATES system and need to be predicted to ensure the reliability of the system. However, high temperature and pressure gradients and dynamic feedback cycles pose challenges on predicting the influence of the relevant processes. Within this study, a reservoir model comprising a coupled hydraulic-thermal-chemical simulation was developed based on an ATES demonstration project located in the city of Berlin, Germany. The structural model was created with Petrel, based on data available from seismic cross-sections and wellbores. The reservoir simulation was realized by combining the capabilities of multiple simulation tools. For the reactive transport model, COMSOL Multiphysics (hydraulic-thermal) and PHREEQC (chemical) were combined using the novel interface COMSOL_PHREEQC, developed by Wissmeier & Barry (2011). It provides a MATLAB-based coupling interface between both programs. Compared to using COMSOL's built-in reactive transport simulator, PHREEQC additionally calculates adsorption and reaction kinetics and allows the selection of different activity coefficient models in the database. The presented simulation tool will be able to predict the most important aspects of hydraulic, thermal and chemical transport processes relevant to

  12. Friction Theory Prediction of Crude Oil Viscosity at Reservoir Conditions Based on Dead Oil Properties

    DEFF Research Database (Denmark)

    Cisneros, Sergio; Zeberg-Mikkelsen, Claus Kjær; Stenby, Erling Halfdan

    2003-01-01

    The general one-parameter friction theory (f-theory) models have been further extended to the prediction of the viscosity of real "live" reservoir fluids based on viscosity measurements of the "dead" oil and the compositional information of the live fluid. This work representation of the viscosity...... of real fluids is obtained by a simple one-parameter tuning of a linear equation derived from a general one-parameter f-theory model. Further, this is achieved using simple cubic equations of state (EOS), such as the Peng-Robinson (PR) EOS or the Soave-Redlich-Kwong (SRK) EOS, which are commonly used...... within the oil industry. In sake of completeness, this work also presents a simple characterization procedure which is based on compositional information of an oil sample. This procedure provides a method for characterizing an oil into a number of compound groups along with the critical constants...

  13. Support vector regression for porosity prediction in a heterogeneous reservoir: A comparative study

    Science.gov (United States)

    Al-Anazi, A. F.; Gates, I. D.

    2010-12-01

    In wells with limited log and core data, porosity, a fundamental and essential property to characterize reservoirs, is challenging to estimate by conventional statistical methods from offset well log and core data in heterogeneous formations. Beyond simple regression, neural networks have been used to develop more accurate porosity correlations. Unfortunately, neural network-based correlations have limited generalization ability and global correlations for a field are usually less accurate compared to local correlations for a sub-region of the reservoir. In this paper, support vector machines are explored as an intelligent technique to correlate porosity to well log data. Recently, support vector regression (SVR), based on the statistical learning theory, have been proposed as a new intelligence technique for both prediction and classification tasks. The underlying formulation of support vector machines embodies the structural risk minimization (SRM) principle which has been shown to be superior to the traditional empirical risk minimization (ERM) principle employed by conventional neural networks and classical statistical methods. This new formulation uses margin-based loss functions to control model complexity independently of the dimensionality of the input space, and kernel functions to project the estimation problem to a higher dimensional space, which enables the solution of more complex nonlinear problem optimization methods to exist for a globally optimal solution. SRM minimizes an upper bound on the expected risk using a margin-based loss function ( ɛ-insensitivity loss function for regression) in contrast to ERM which minimizes the error on the training data. Unlike classical learning methods, SRM, indexed by margin-based loss function, can also control model complexity independent of dimensionality. The SRM inductive principle is designed for statistical estimation with finite data where the ERM inductive principle provides the optimal solution (the

  14. Quantifying the uncertainties of climate change effects on the storage-yield and performance characteristics of the Pong multi-purpose reservoir, India

    Directory of Open Access Journals (Sweden)

    B. Soundharajan

    2015-06-01

    Full Text Available Climate change is predicted to affect water resources infrastructure due to its effect on rainfall, temperature and evapotranspiration. However, there are huge uncertainties on both the magnitude and direction of these effects. The Pong reservoir on the Beas River in northern India serves irrigation and hydropower needs. The hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall; the changing pattern of the latter and the predicted disappearance of the former will have profound effects on the performance of the reservoir. This study employed a Monte-Carlo simulation approach to characterise the uncertainties in the future storage requirements and performance of the reservoir. Using a calibrated rainfall-runoff (R-R model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change perturbed future scenarios. The resulting runoff ensembles were used to simulate the behaviour of the reservoir and determine "populations" of reservoir storage capacity and performance characteristics. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the uncertainties. The results show that contrary to the usual practice of using single records, there is wide variability in the assessed impacts. This variability or uncertainty will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of its sheer magnitude as demonstrated in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.

  15. Predictive modeling of CO2 sequestration in deep saline sandstone reservoirs: Impacts of geochemical kinetics

    Energy Technology Data Exchange (ETDEWEB)

    Balashov, Victor N.; Guthrie, George D.; Hakala, J. Alexandra; Lopano, Christina L.; Rimstidt, J. Donald; Brantley, Susan L.

    2013-03-01

    One idea for mitigating the increase in fossil-fuel generated CO{sub 2} in the atmosphere is to inject CO{sub 2} into subsurface saline sandstone reservoirs. To decide whether to try such sequestration at a globally significant scale will require the ability to predict the fate of injected CO{sub 2}. Thus, models are needed to predict the rates and extents of subsurface rock-water-gas interactions. Several reactive transport models for CO{sub 2} sequestration created in the last decade predicted sequestration in sandstone reservoirs of ~17 to ~90 kg CO{sub 2} m{sup -3|. To build confidence in such models, a baseline problem including rock + water chemistry is proposed as the basis for future modeling so that both the models and the parameterizations can be compared systematically. In addition, a reactive diffusion model is used to investigate the fate of injected supercritical CO{sub 2} fluid in the proposed baseline reservoir + brine system. In the baseline problem, injected CO{sub 2} is redistributed from the supercritical (SC) free phase by dissolution into pore brine and by formation of carbonates in the sandstone. The numerical transport model incorporates a full kinetic description of mineral-water reactions under the assumption that transport is by diffusion only. Sensitivity tests were also run to understand which mineral kinetics reactions are important for CO{sub 2} trapping. The diffusion transport model shows that for the first ~20 years after CO{sub 2} diffusion initiates, CO{sub 2} is mostly consumed by dissolution into the brine to form CO{sub 2,aq} (solubility trapping). From 20-200 years, both solubility and mineral trapping are important as calcite precipitation is driven by dissolution of oligoclase. From 200 to 1000 years, mineral trapping is the most important sequestration mechanism, as smectite dissolves and calcite precipitates. Beyond 2000 years, most trapping is due to formation of aqueous HCO{sub 3}{sup -}. Ninety-seven percent of the

  16. Predictability of Western Himalayan river flow: melt seasonal inflow into Bhakra Reservoir in northern India

    Directory of Open Access Journals (Sweden)

    I. Pal

    2013-06-01

    Full Text Available Snowmelt-dominated streamflow of the Western Himalayan rivers is an important water resource during the dry pre-monsoon spring months to meet the irrigation and hydropower needs in northern India. Here we study the seasonal prediction of melt-dominated total inflow into the Bhakra Dam in northern India based on statistical relationships with meteorological variables during the preceding winter. Total inflow into the Bhakra Dam includes the Satluj River flow together with a flow diversion from its tributary, the Beas River. Both are tributaries of the Indus River that originate from the Western Himalayas, which is an under-studied region. Average measured winter snow volume at the upper-elevation stations and corresponding lower-elevation rainfall and temperature of the Satluj River basin were considered as empirical predictors. Akaike information criteria (AIC and Bayesian information criteria (BIC were used to select the best subset of inputs from all the possible combinations of predictors for a multiple linear regression framework. To test for potential issues arising due to multicollinearity of the predictor variables, cross-validated prediction skills of the best subset were also compared with the prediction skills of principal component regression (PCR and partial least squares regression (PLSR techniques, which yielded broadly similar results. As a whole, the forecasts of the melt season at the end of winter and as the melt season commences were shown to have potential skill for guiding the development of stochastic optimization models to manage the trade-off between irrigation and hydropower releases versus flood control during the annual fill cycle of the Bhakra Reservoir, a major energy and irrigation source in the region.

  17. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  18. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

    Science.gov (United States)

    Jothiprakash, V.; Magar, R. B.

    2012-07-01

    SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

  19. The Real World Significance of Performance Prediction

    Science.gov (United States)

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  20. An Approximate Solution for Predicting the Heat Extraction and Preventing Heat Loss from a Closed-Loop Geothermal Reservoir

    Directory of Open Access Journals (Sweden)

    Bisheng Wu

    2017-01-01

    Full Text Available Approximate solutions are found for a mathematical model developed to predict the heat extraction from a closed-loop geothermal system which consists of two vertical wells (one for injection and the other for production and one horizontal well which connects the two vertical wells. Based on the feature of slow heat conduction in rock formation, the fluid flow in the well is divided into three stages, that is, in the injection, horizontal, and production wells. The output temperature of each stage is regarded as the input of the next stage. The results from the present model are compared with those obtained from numerical simulator TOUGH2 and show first-order agreement with a temperature difference less than 4°C for the case where the fluid circulated for 2.74 years. In the end, a parametric study shows that (1 the injection rate plays dominant role in affecting the output performance, (2 higher injection temperature produces larger output temperature but decreases the total heat extracted given a specific time, (3 the output performance of geothermal reservoir is insensitive to fluid viscosity, and (4 there exists a critical point that indicates if the fluid releases heat into or absorbs heat from the surrounding formation.

  1. Design Techniques and Reservoir Simulation

    Directory of Open Access Journals (Sweden)

    Ahad Fereidooni

    2012-11-01

    Full Text Available Enhanced oil recovery using nitrogen injection is a commonly applied method for pressure maintenance in conventional reservoirs. Numerical simulations can be practiced for the prediction of a reservoir performance in the course of injection process; however, a detailed simulation might take up enormous computer processing time. In such cases, a simple statistical model may be a good approach to the preliminary prediction of the process without any application of numerical simulation. In the current work, seven rock/fluid reservoir properties are considered as screening parameters and those parameters having the most considerable effect on the process are determined using the combination of experimental design techniques and reservoir simulations. Therefore, the statistical significance of the main effects and interactions of screening parameters are analyzed utilizing statistical inference approaches. Finally, the influential parameters are employed to create a simple statistical model which allows the preliminary prediction of nitrogen injection in terms of a recovery factor without resorting to numerical simulations.

  2. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  3. Evaporation suppression from water reservoirs using floating covers: Lab scale observations and model predictions

    Science.gov (United States)

    Or, D.; Lehmann, P.; Aminzadeh, M.; Sommer, M.; Wey, H.; Wunderli, H.; Breitenstein, D.

    2016-12-01

    The competition over dwindling fresh water resources is expected to intensify with projected increase in human population in arid regions, expansion of irrigated land and changes in climate and drought patterns. The volume of water stored in reservoirs would also increase to mitigate seasonal shortages due to rainfall variability and to meet irrigation water needs. By some estimates up to half of the stored water is lost to evaporation thereby exacerbating the water scarcity problem. Recently, there is an upsurge in the use of self-assembling floating covers to suppress evaporation, yet the design, and implementation remain largely empirical. Studies have shown that evaporation suppression is highly nonlinear, as also known from a century of research on gas exchange from plant leaves (that often evaporate as free water surfaces through stomata that are only 1% of leaf area). We report a systematic evaluation of different cover types and external drivers (radiation, wind, wind+radiation) on evaporation suppression and energy balance of a 1.4 m2 basin placed in a wind-tunnel. Surprisingly, evaporation suppression by black and white floating covers (balls and plates) were similar despite significantly different energy balance regimes over the cover surfaces. Moreover, the evaporation suppression efficiency was a simple function of the uncovered area (square root of the uncovered fraction) with linear relations with the covered area in some cases. The thermally decoupled floating covers offer an efficient solution to the evaporation suppression with limited influence of the surface energy balance (water temperature for black and white covers was similar and remained nearly constant). The results will be linked with a predictive evaporation-energy balance model and issues of spatial scales and long exposure times will be studied.

  4. Real-Time Predictions of Reservoir Size and Rebound Time during Antiretroviral Therapy Interruption Trials for HIV.

    Directory of Open Access Journals (Sweden)

    Alison L Hill

    2016-04-01

    Full Text Available Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients-between 40 and 150-will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two "Boston patients", recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV+ cells in the recipient versus newly infected cells from the donor made to the

  5. Pre-drilling prediction techniques on the high-temperature high-pressure hydrocarbon reservoirs offshore Hainan Island, China

    Science.gov (United States)

    Zhang, Hanyu; Liu, Huaishan; Wu, Shiguo; Sun, Jin; Yang, Chaoqun; Xie, Yangbing; Chen, Chuanxu; Gao, Jinwei; Wang, Jiliang

    2018-02-01

    Decreasing the risks and geohazards associated with drilling engineering in high-temperature high-pressure (HTHP) geologic settings begins with the implementation of pre-drilling prediction techniques (PPTs). To improve the accuracy of geopressure prediction in HTHP hydrocarbon reservoirs offshore Hainan Island, we made a comprehensive summary of current PPTs to identify existing problems and challenges by analyzing the global distribution of HTHP hydrocarbon reservoirs, the research status of PPTs, and the geologic setting and its HTHP formation mechanism. Our research results indicate that the HTHP formation mechanism in the study area is caused by multiple factors, including rapid loading, diapir intrusions, hydrocarbon generation, and the thermal expansion of pore fluids. Due to this multi-factor interaction, a cloud of HTHP hydrocarbon reservoirs has developed in the Ying-Qiong Basin, but only traditional PPTs have been implemented, based on the assumption of conditions that do not conform to the actual geologic environment, e.g., Bellotti's law and Eaton's law. In this paper, we focus on these issues, identify some challenges and solutions, and call for further PPT research to address the drawbacks of previous works and meet the challenges associated with the deepwater technology gap. In this way, we hope to contribute to the improved accuracy of geopressure prediction prior to drilling and provide support for future HTHP drilling offshore Hainan Island.

  6. Assessment of Short Term Flood Operation Strategies Using Numerical Weather Prediction Data in YUVACΙK DAM Reservoir, Turkey

    Science.gov (United States)

    Uysal, G.; Yavuz, O.; Sensoy, A.; Sorman, A.; Akgun, T.; Gezgin, T.

    2011-12-01

    first step, a hydrological model with an embedded snow module is used to establish a rainfall-runoff relationship to calculate the inflow into the dam reservoir. The basin is divided into four sub-basins, along with the three elevation zones for each subbasin. Hydro-meteorological data are collected via 11 automated stations in and around the basin and a semi-distributed rainfall-runoff model, HEC-HMS, is calibrated for sub-basins. Then, HEC-ResSim is used to create simulation alternatives of reservoir system according to user defined guide curves and rules based on internal and/or external variables. The decision support modeling scenarios are tested with Numerical Weather Prediction Mesoscale Model 5 (MM5) daily total precipitation and daily average temperature data. Predicted precipitation and temperature data are compared with ground observations to examine the consistency. Predicted inflows computed by HEC-HMS are used as main forcing inputs into HEC-ResSim for the short term operation of reservoir during the flood events.

  7. A prediction of Power Duration Curve from the Optimal Operation of the Multi Reservoirs System

    Directory of Open Access Journals (Sweden)

    Abdul Wahab Younis

    2013-04-01

    Full Text Available  This study aims of predication Power Duration Curves(PDC resulting from the optimal operation of the multi reservoirs system which comprises the reservoirs of Bakhma dam,Dokan dam and Makhool dam for the division of years over 30 years.Discrete Differential Dynamic Programming(DDDP has been employed to find the optimal operation of the said reservoirs.    PDC representing the relationship between the generated hydroelectric power and percentage of operation time equaled or exceeded . The importance of these curves lies in knowing the volume of electric power available for that percentage of operation time. The results have shown that the sum of yearly hydroelectric power for average Release and for the single operation was 5410,1604,2929(Mwfor the reservoirs of Bakhma, Dokan, Makhool dams, which resulted from the application of independent DDDP technology. Also, the hydroelectric power whose generation can be guranteed for 90% of the time is 344.91,107.7,188.15 (Mw for the single operation and 309.1,134.08,140.7 (Mw for the operation as a one system for the reservoirs of Bakhma, Dokan, and Makhool dams respectively.

  8. Performance of Surfactant Methyl Ester Sulphonate solution for Oil Well Stimulation in reservoir sandstone TJ Field

    Science.gov (United States)

    Eris, F. R.; Hambali, E.; Suryani, A.; Permadi, P.

    2017-05-01

    Asphaltene, paraffin, wax and sludge deposition, emulsion and water blocking are kinds ofprocess that results in a reduction of the fluid flow from the reservoir into formation which causes a decrease of oil wells productivity. Oil well Stimulation can be used as an alternative to solve oil well problems. Oil well stimulation technique requires applying of surfactant. Sodium Methyl Ester Sulphonate (SMES) of palm oil is an anionic surfactant derived from renewable natural resource that environmental friendly is one of potential surfactant types that can be used in oil well stimulation. This study was aimed at formulation SMES as well stimulation agent that can identify phase transitions to phase behavior in a brine-surfactant-oil system and altered the wettability of rock sandstone and limestone. Performance of SMES solution tested by thermal stability test, phase behavioral examination and rocks wettability test. The results showed that SMES solution (SMES 5% + xylene 5% in the diesel with addition of 1% NaCl at TJformation water and SMES 5% + xylene 5% in methyl ester with the addition of NaCl 1% in the TJ formation water) are surfactant that can maintain thermal stability, can mostly altered the wettability toward water-wet in sandstone reservoir, TJ Field.

  9. Rational Rock Physics for Improved Velocity Prediction and Reservoir Properties Estimation for Granite Wash (Tight Sands in Anadarko Basin, Texas

    Directory of Open Access Journals (Sweden)

    Muhammad Z. A. Durrani

    2014-01-01

    Full Text Available Due to the complex nature, deriving elastic properties from seismic data for the prolific Granite Wash reservoir (Pennsylvanian age in the western Anadarko Basin Wheeler County (Texas is quite a challenge. In this paper, we used rock physics tool to describe the diagenesis and accurate estimation of seismic velocities of P and S waves in Granite Wash reservoir. Hertz-Mindlin and Cementation (Dvorkin’s theories are applied to analyze the nature of the reservoir rocks (uncemented and cemented. In the implementation of rock physics diagnostics, three classical rock physics (empirical relations, Kuster-Toksöz, and Berryman models are comparatively analyzed for velocity prediction taking into account the pore shape geometry. An empirical (VP-VS relationship is also generated calibrated with core data for shear wave velocity prediction. Finally, we discussed the advantages of each rock physics model in detail. In addition, cross-plots of unconventional attributes help us in the clear separation of anomalous zone and lithologic properties of sand and shale facies over conventional attributes.

  10. Predicting Performance Ratings Using Motivational Antecedents

    National Research Council Canada - National Science Library

    Zazania, Michelle

    1998-01-01

    This research examined the role of motivation in predicting peer and trainer ratings of student performance and contrasted the relative importance of various antecedents for peer and trainer ratings...

  11. A mathematical model of reservoir sediment quality prediction based on land-use and erosion processes in watershed

    Science.gov (United States)

    Junakova, N.; Balintova, M.; Junak, J.

    2017-10-01

    The aim of this paper is to propose a mathematical model for determining of total nitrogen (N) and phosphorus (P) content in eroded soil particles with emphasis on prediction of bottom sediment quality in reservoirs. The adsorbed nutrient concentrations are calculated using the Universal Soil Loss Equation (USLE) extended by the determination of the average soil nutrient concentration in top soils. The average annual vegetation and management factor is divided into five periods of the cropping cycle. For selected plants, the average plant nutrient uptake divided into five cropping periods is also proposed. The average nutrient concentrations in eroded soil particles in adsorbed form are modified by sediment enrichment ratio to obtain the total nutrient content in transported soil particles. The model was designed for the conditions of north-eastern Slovakia. The study was carried out in the agricultural basin of the small water reservoir Klusov.

  12. The modified SWAT model for predicting fecal coliform in the Wachusett Reservoir Watershed, USA

    Science.gov (United States)

    Fecal contamination has been an issue for water quality because fecal coliform bacteria are used as an indicator organism to detect pathogens in water. In order to assess fecal contamination in the Wachusett Reservoir Watershed in Massachusetts, USA, the Soil and Water Assessment Tool (SWAT), a comm...

  13. Complexity factors and prediction of performance

    International Nuclear Information System (INIS)

    Braarud, Per Oeyvind

    1998-03-01

    Understanding of what makes a control room situation difficult to handle is important when studying operator performance, both with respect to prediction as well as improvement of the human performance. A factor analytic approach identified eight factors from operators' answers to an 39 item questionnaire about complexity of the operator's task in the control room. A Complexity Profiling Questionnaire was developed, based on the factor analytic results from the operators' conception of complexity. The validity of the identified complexity factors was studied by prediction of crew performance and prediction of plant performance from ratings of the complexity of scenarios. The scenarios were rated by both process experts and the operators participating in the scenarios, using the Complexity Profiling Questionnaire. The process experts' complexity ratings predicted both crew performance and plant performance, while the operators' rating predicted plant performance only. The results reported are from initial studies of complexity, and imply a promising potential for further studies of the concept. The approach used in the study as well as the reported results are discussed. A chapter about the structure of the conception of complexity, and a chapter about further research conclude the report. (author)

  14. Investigation on the effect of the reservoir variables and operational parameters on SAGD performance

    Energy Technology Data Exchange (ETDEWEB)

    Hashemi Kiasari, H.; Naderifar, A. [AmirKabir University of Technology, Tehran (Iran, Islamic Republic of). Petroleum Engineering Dept.; Sedaee Sola, B. [University of Tehran (Iran, Islamic Republic of). Faculty of Engineering. Inst. of Petroleum Engineering], e-mail: sedaeesola@yahoo.com

    2010-04-15

    Steam injection is the most important thermal enhanced oil recovery method. One typical procedure is Steam- Assisted Gravity Drainage (SAGD), which is a promising recovery process to produce heavy oil and bitumen. The method ensures a stable displacement of steam at economical rates by using gravity as the driving force and a pair of horizontal wells for injection/production. There are numerous studies done on SAGD in conventional reservoirs, but the majority of them focus on the investigation of the process in microscopic scale. In this study, we investigate the SAGD process with a preheating period, using steam circulation in well pair on a field scale. The synthetic homogenous model was constructed by CMG and simulated using the STARS module. The effects of operational parameters, such as preheating period, vertical well spacing, well pair length, steam quality and production pressure, and reservoir variables, such as rock porosity and permeability, vertical-to-horizontal permeability ratio, thermal conductivity of the formation and rock heat capacity, on the SAGD performance were investigated. The results show that the preheating period affects mainly the initial stages of production. Due to preheating, the well pair communication with the higher vertical distances is also established; therefore, there was no considerable difference between oil productions in various well spacing cases. As steam quality increases, the oil production in later production times also increases. At shorter well pair, more steam can be injected per unit length of well, but, on the other hand, the production well recovers less heated oil area; therefore the well pair length should be optimized in all cases. By decreasing the production well bottom-hole pressure, more heated oil in near well region is produced; therefore, the injected steam raises more in the depleted area. The results of the simulations show that very low permeability leads to a fully unsuccessful SAGD process. In the

  15. Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

    Science.gov (United States)

    Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

    2014-05-01

    Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

  16. A GIS-model for predicting the impact of climate change on shore erosion in hydroelectric reservoirs

    International Nuclear Information System (INIS)

    Penner, L.A.; Zimmer, T.A.M.; St Laurent, M.

    2008-01-01

    Shoreline erosion affects inland lakes and hydroelectric reservoirs in several ways. This poster described a vector-based geographic information system (GIS) model designed to predict changes in shore zone geometry, top-of-bluff recession, and eroded sediment volumes. The model was designed for use in Manitoba Hydro's reservoirs in northern Manitoba, and simulated near-shore downcutting and bank recession caused by wind-generated waves. Parameters for the model included deep water wave energy, and water level fluctuations. Effective wave energy was seen as a function of the water level fluctuation range, wave conditions, and near-shore slope. The model was validated by field monitoring studies that included repeated shore zone transect surveys and sediment coring studies. Results of the study showed that the model provides a systematic method of predicting potential changes in erosion associated with climatic change. The volume and mass of eroded sediment predicted for the different modelling scenarios will be used as input data for future sedimentation models. tabs., figs

  17. Assessing reservoir performance risk in CO{sub 2} storage projects

    Energy Technology Data Exchange (ETDEWEB)

    Bowden, A.R. [URS Corp., San Francisco, CA (United States); Rigg, A. [CRC for Greenhouse Gas Technologies, Canberra (Australia)

    2005-07-01

    One of the main issues for researchers involved with geological storage of carbon dioxide (CO{sub 2}) has been the development of a proper methodology to assess and compare alternative CO{sub 2} injection projects on the basis of risk. Consideration needs to be given to technical aspects, such as the risk of leakage and the effectiveness of the intended reservoir, as well as less tangible aspects such as the value and safety of geological storage of CO{sub 2}, and potential impacts on the community and environment. The Geological Disposal of Carbon Dioxide (GEODISC), was a research program of the Australian Petroleum Cooperative Research Centre which identified 56 potential environmentally sustainable sites for CO{sub 2} injection (ESSCIs) within Australia. Several studies were carried out, involving detailed evaluation of the suitability of 4 selected sites, including Dongara, Petrel, Gippsland and Carnarvon. The GEODISC program included a risk assessment research module which required a complete and quantified risk assessment of CO{sub 2} injection as a storage option. Primary goals were to assess the risk of leakage, to assess the effectiveness of the intended reservoir, and to assess negative consequences to facilitate comparison of alternative sites. This paper discussed the background and risk assessment model. Key performance indicators (KPIs) were also developed to address the purpose of risk assessment. It was concluded that the RISQUE method is an appropriate approach and that potential injection projects can be measured against six KPIs including containment; effectiveness; self-funding potential; wider community benefits; community safety and community amenity. 6 refs., 3 tabs., 3 figs.

  18. A new method in predicting productivity of multi-stage fractured horizontal well in tight gas reservoirs

    Directory of Open Access Journals (Sweden)

    Yunsheng Wei

    2016-10-01

    Full Text Available The generally accomplished technique for horizontal wells in tight gas reservoirs is by multi-stage hydraulic fracturing, not to mention, the flow characteristics of a horizontal well with multiple transverse fractures are very intricate. Conventional methods, well as an evaluation unit, are difficult to accurately predict production capacity of each fracture and productivity differences between wells with a different number of fractures. Thus, a single fracture sets the minimum evaluation unit, matrix, fractures, and lateral wellbore model that are then combined integrally to approximate horizontal well with multiple transverse hydraulic fractures in tight gas reservoirs. This paper presents a new semi-analytical methodology for predicting the production capacity of a horizontal well with multiple transverse hydraulic fractures in tight gas reservoirs. Firstly, a mathematical flow model used as a medium, which is disturbed by finite conductivity vertical fractures and rectangular shaped boundaries, is established and explained by the Fourier integral transform. Then the idea of a single stage fracture analysis is incorporated to establish linear flow model within a single fracture with a variable rate. The Fredholm integral numerical solution is applicable for the fracture conductivity function. Finally, the pipe flow model along the lateral wellbore is adapted to couple multi-stages fracture mathematical models, and the equation group of predicting productivity of a multi-stage fractured horizontal well. The whole flow process from the matrix to bottom-hole and production interference between adjacent fractures is also established. Meanwhile, the corresponding iterative algorithm of the equations is given. In this case analysis, the productions of each well and fracture are calculated under the different bottom-hole flowing pressure, and this method also contributes to obtaining the distribution of pressure drop and production for every

  19. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  20. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  1. Genomic Prediction of Barley Hybrid Performance

    Directory of Open Access Journals (Sweden)

    Norman Philipp

    2016-07-01

    Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

  2. Prediction of total organic carbon content in shale reservoir based on a new integrated hybrid neural network and conventional well logging curves

    Science.gov (United States)

    Zhu, Linqi; Zhang, Chong; Zhang, Chaomo; Wei, Yang; Zhou, Xueqing; Cheng, Yuan; Huang, Yuyang; Zhang, Le

    2018-06-01

    There is increasing interest in shale gas reservoirs due to their abundant reserves. As a key evaluation criterion, the total organic carbon content (TOC) of the reservoirs can reflect its hydrocarbon generation potential. The existing TOC calculation model is not very accurate and there is still the possibility for improvement. In this paper, an integrated hybrid neural network (IHNN) model is proposed for predicting the TOC. This is based on the fact that the TOC information on the low TOC reservoir, where the TOC is easy to evaluate, comes from a prediction problem, which is the inherent problem of the existing algorithm. By comparing the prediction models established in 132 rock samples in the shale gas reservoir within the Jiaoshiba area, it can be seen that the accuracy of the proposed IHNN model is much higher than that of the other prediction models. The mean square error of the samples, which were not joined to the established models, was reduced from 0.586 to 0.442. The results show that TOC prediction is easier after logging prediction has been improved. Furthermore, this paper puts forward the next research direction of the prediction model. The IHNN algorithm can help evaluate the TOC of a shale gas reservoir.

  3. WETTABILITY AND PREDICTION OF OIL RECOVERY FROM RESERVOIRS DEVELOPED WITH MODERN DRILLING AND COMPLETION FLUIDS

    Energy Technology Data Exchange (ETDEWEB)

    Jill S. Buckley; Norman R. Morrow

    2006-01-01

    The objectives of this project are: (1) to improve understanding of the wettability alteration of mixed-wet rocks that results from contact with the components of synthetic oil-based drilling and completion fluids formulated to meet the needs of arctic drilling; (2) to investigate cleaning methods to reverse the wettability alteration of mixed-wet cores caused by contact with these SBM components; and (3) to develop new approaches to restoration of wetting that will permit the use of cores drilled with SBM formulations for valid studies of reservoir properties.

  4. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  5. Predicting the life-cycle performance of an EGS by numerical simulation

    Science.gov (United States)

    Blöcher, G.; Zimmermann, G.; Moeck, I.; Brandt, W.; Huenges, E.

    2009-04-01

    Enhanced geothermal systems (EGS) are engineered reservoirs that have been created to extract economical amounts of heat from low permeability and/or porosity geothermal resources. Reservoir engineering requires a comprehensive data base of reservoir parameters to perform reservoir simulations and it implies reservoir characterisation, production enhancement through stimulation techniques and assurance of the resource-sustainability. This study addresses the hydro-thermal (HT) conditions of the geothermal research doublet E GrSk03/90 and Gt GrSk04/05 at the drill site Gross Schoenebeck (north of Berlin, Germany). The first well Gross Schoenebeck E GrSk3/90 was tested to investigate scenarios of enhancing productivity of thermal fluid recovery from the underground. In order to complete the doublet system a second well Gt GrSk4/05 with a true vertical depth of -4198 m has been finished in 2007, followed by three stimulation treatments to enhance productivity. In order to increase the apparent thickness of the reservoir horizon, the new well is inclined in the reservoir section by 48° and was drilled in the direction of the minimum horizontal stress (Sh=288° azimuth) for optimum hydraulic fracture alignment in relation to the stimulated pre-existing well EGrSk3/90. Hence the orientation of the fractures will be 18° azimuth in the direction of the maximum horizontal stress. The reservoir is located at 4100-4300 m depth within the Lower Permian of the North East German Basin. According to the continental geothermal gradient, the reservoir temperature increases from 138°C to 147°C from top to bottom. In order to get evidence of the hydraulic-thermal (HT) behaviour of the geothermal reservoir during the time of geothermal power production a 3D model was developed. This model includes coupling of various petrophysical parameters: specifically, temperature dependent heat conductivity and heat capacity are considered. The porosity and hydraulic conductivity of the rock

  6. Fracture Evolution Following a Hydraulic Stimulation within an EGS Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Mella, Michael [Univ. of Utah, Salt Lake City, UT (United States). Energy and Geoscience Inst.

    2016-08-31

    The objective of this project was to develop and demonstrate an approach for tracking the evolution of circulation immediately following a hydraulic stimulation in an EGS reservoir. Series of high-resolution tracer tests using conservative and thermally reactive tracers were designed at recently created EGS reservoirs in order to track changes in fluid flow parameters such as reservoir pore volume, flow capacity, and effective reservoir temperature over time. Data obtained from the project would be available for the calibration of reservoir models that could serve to predict EGS performance following a hydraulic stimulation.

  7. Seismic prediction on the favorable efficient development areas of the Longwangmiao Fm gas reservoir in the Gaoshiti–Moxi area, Sichuan Basin

    Directory of Open Access Journals (Sweden)

    Guangrong Zhang

    2017-05-01

    Full Text Available The Lower Cambrian Longwangmiao Fm gas reservoir in the Gaoshiti–Moxi area, the Sichuan Basin, is a super giant monoblock marine carbonate gas reservoir with its single size being the largest in China. The key to the realization of high and stable production gas wells in this gas reservoir is to identify accurately high-permeability zones where there are dissolved pores or dissolved pores are superimposed with fractures. However, high quality dolomite reservoirs are characterized by large burial depth and strong heterogeneity, so reservoir prediction is of difficult. In this paper, related seismic researches were carried out and supporting technologies were developed as follows. First, a geologic model was built after an analysis of the existing data and forward modeling was carried out to establish a reservoir seismic response model. Second, by virtue of well-oriented amplitude processing technology, spherical diffusion compensation factor was obtained based on VSP well logging data and the true amplitude of seismic data was recovered. Third, the resolution of deep seismic data was improved by using the well-oriented high-resolution frequency-expanding technology and prestack time migration data of high quality was acquired. And fourth, multiple shoal facies reservoirs were traced by using the global automatic seismic interpretation technology which is based on stratigraphic model, multiple reservoirs which are laterally continuous and vertically superimposed could be predicted, and the areal distribution of high quality reservoirs could be described accurately and efficiently. By virtue of the supporting technologies, drilling trajectory is positioned accurately, and the deployed development wells all have high yield. These technologies also promote the construction of a modern supergiant gas field of tens of billions of cubic meters.

  8. Heavy oil reservoir evaluation : performing an injection test using DST tools in the marine region of Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Loaiza, J.; Ruiz, P. [Halliburton, Mexico City (Mexico); Barrera, D.; Gutierrez, F. [Pemex, Mexico City (Mexico)

    2010-07-01

    This paper described an injection test conducted to evaluate heavy oil reserves in an offshore area of Mexico. The drill-stem testing (DST) evaluation used a fluid injection technique in order to eliminate the need for artificial lift and coiled tubing. A pressure transient analysis method was used to determine the static pressure of the reservoir, effective hydrocarbon permeability, and formation damage. Boundary effects were also characterized. The total volume of the fluid injection was determined by analyzing various reservoir parameters. The timing of the shut-in procedure was determined by characterizing rock characteristics and fluids within the reservoir. The mobility and diffusivity relationships between the zones with the injection fluids and reservoir fluids were used to defined sweep fluids. A productivity analysis was used to predict various production scenarios. DST tools were then used to conduct a pressure-production assessment. Case histories were used to demonstrate the method. The studies showed that the method provides a cost-effective means of providing high quality data for productivity analyses. 4 refs., 2 tabs., 15 figs.

  9. Plant corrosion: prediction of materials performance

    International Nuclear Information System (INIS)

    Strutt, J.E.; Nicholls, J.R.

    1987-01-01

    Seventeen papers have been compiled forming a book on computer-based approaches to corrosion prediction in a wide range of industrial sectors, including the chemical, petrochemical and power generation industries. Two papers have been selected and indexed separately. The first describes a system operating within BNFL's Reprocessing Division to predict materials performance in corrosive conditions to aid future plant design. The second describes the truncation of the distribution function of pit depths during high temperature oxidation of a 20Cr austenitic steel in the fuel cladding in AGR systems. (U.K.)

  10. Hanford grout: predicting long-term performance

    International Nuclear Information System (INIS)

    Sewart, G.H.; Mitchell, D.H.; Treat, R.L.; McMakin, A.H.

    1987-01-01

    Grouted disposal is being planned for the low-level portion of liquid radioactive wastes at the Hanford site in Washington state. The performance of the disposal system must be such that it will protect people and the environment for thousands of years after disposal. To predict whether a specific grout disposal system will comply with existing and foreseen regulations, a performance assessment (PA) is performed. Long-term PAs are conducted for a range of performance conditions. Performance assessment is an inexact science. Quantifying projected impacts is especially difficult when only scant data exist on the behavior of certain components of the disposal system over thousands of years. To develop defensible results, we are honing the models and obtaining experimental data. The combination of engineered features and PA refinements is being used to ensure that Hanford grout will meet its principal goal: to protect people and the environment in the future

  11. What predicts performance during clinical psychology training?

    OpenAIRE

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2013-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

  12. Assessing Performance of Multipurpose Reservoir System Using Two-Point Linear Hedging Rule

    Science.gov (United States)

    Sasireka, K.; Neelakantan, T. R.

    2017-07-01

    Reservoir operation is the one of the important filed of water resource management. Innovative techniques in water resource management are focussed at optimizing the available water and in decreasing the environmental impact of water utilization on the natural environment. In the operation of multi reservoir system, efficient regulation of the release to satisfy the demand for various purpose like domestic, irrigation and hydropower can lead to increase the benefit from the reservoir as well as significantly reduces the damage due to floods. Hedging rule is one of the emerging techniques in reservoir operation, which reduce the severity of drought by accepting number of smaller shortages. The key objective of this paper is to maximize the minimum power production and improve the reliability of water supply for municipal and irrigation purpose by using hedging rule. In this paper, Type II two-point linear hedging rule is attempted to improve the operation of Bargi reservoir in the Narmada basin in India. The results obtained from simulation of hedging rule is compared with results from Standard Operating Policy, the result shows that the application of hedging rule significantly improved the reliability of water supply and reliability of irrigation release and firm power production.

  13. Predicting sample size required for classification performance

    Directory of Open Access Journals (Sweden)

    Figueroa Rosa L

    2012-02-01

    Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

  14. Mapping of Reservoir Properties and Facies Through Integration of Static and Dynamic Data

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, Albert C.; Oliver, Dean S.; Zhang, Fengjun; Dong, Yannong; Skjervheim, Jan Arild; Liu, Ning

    2003-03-10

    The goal of this project was to develop computationally efficient automatic history matching techniques for generating geologically plausible reservoir models which honor both static and dynamic data. Solution of this problem was necessary for the quantification of uncertainty in future reservoir performance predictions and for the optimization of reservoir management.

  15. Mapping of Reservoir Properties and Facies Through Integration of Static and Dynamic Data

    Energy Technology Data Exchange (ETDEWEB)

    Oliver, Dean S.; Reynolds, Albert C.; Zhang, Fengjun; Li, Ruijian; Abacioglu, Yafes; Dong, Yannong

    2002-03-05

    The goal of this project was to develop computationally efficient automatic history matching techniques for generating geologically plausible reservoir models which honor both static and dynamic data. Solution of this problem is necessary for the quantification of uncertainty in future reservoir performance predictions and for the optimization of reservoir management.

  16. Estimating Western U.S. Reservoir Sedimentation

    Science.gov (United States)

    Bensching, L.; Livneh, B.; Greimann, B. P.

    2017-12-01

    Reservoir sedimentation is a long-term problem for water management across the Western U.S. Observations of sedimentation are limited to reservoir surveys that are costly and infrequent, with many reservoirs having only two or fewer surveys. This work aims to apply a recently developed ensemble of sediment algorithms to estimate reservoir sedimentation over several western U.S. reservoirs. The sediment algorithms include empirical, conceptual, stochastic, and processes based approaches and are coupled with a hydrologic modeling framework. Preliminary results showed that the more complex and processed based algorithms performed better in predicting high sediment flux values and in a basin transferability experiment. However, more testing and validation is required to confirm sediment model skill. This work is carried out in partnership with the Bureau of Reclamation with the goal of evaluating the viability of reservoir sediment yield prediction across the western U.S. using a multi-algorithm approach. Simulations of streamflow and sediment fluxes are validated against observed discharges, as well as a Reservoir Sedimentation Information database that is being developed by the US Army Corps of Engineers. Specific goals of this research include (i) quantifying whether inter-algorithm differences consistently capture observational variability; (ii) identifying whether certain categories of models consistently produce the best results, (iii) assessing the expected sedimentation life-span of several western U.S. reservoirs through long-term simulations.

  17. Large reservoirs: Chapter 17

    Science.gov (United States)

    Miranda, Leandro E.; Bettoli, Phillip William

    2010-01-01

    Large impoundments, defined as those with surface area of 200 ha or greater, are relatively new aquatic ecosystems in the global landscape. They represent important economic and environmental resources that provide benefits such as flood control, hydropower generation, navigation, water supply, commercial and recreational fisheries, and various other recreational and esthetic values. Construction of large impoundments was initially driven by economic needs, and ecological consequences received little consideration. However, in recent decades environmental issues have come to the forefront. In the closing decades of the 20th century societal values began to shift, especially in the developed world. Society is no longer willing to accept environmental damage as an inevitable consequence of human development, and it is now recognized that continued environmental degradation is unsustainable. Consequently, construction of large reservoirs has virtually stopped in North America. Nevertheless, in other parts of the world construction of large reservoirs continues. The emergence of systematic reservoir management in the early 20th century was guided by concepts developed for natural lakes (Miranda 1996). However, we now recognize that reservoirs are different and that reservoirs are not independent aquatic systems inasmuch as they are connected to upstream rivers and streams, the downstream river, other reservoirs in the basin, and the watershed. Reservoir systems exhibit longitudinal patterns both within and among reservoirs. Reservoirs are typically arranged sequentially as elements of an interacting network, filter water collected throughout their watersheds, and form a mosaic of predictable patterns. Traditional approaches to fisheries management such as stocking, regulating harvest, and in-lake habitat management do not always produce desired effects in reservoirs. As a result, managers may expend resources with little benefit to either fish or fishing. Some locally

  18. Predicting the performance of fingerprint similarity searching.

    Science.gov (United States)

    Vogt, Martin; Bajorath, Jürgen

    2011-01-01

    Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.

  19. Geothermal Reservoir Technology Research Program: Abstracts of selected research projects

    Energy Technology Data Exchange (ETDEWEB)

    Reed, M.J. (ed.)

    1993-03-01

    Research projects are described in the following areas: geothermal exploration, mapping reservoir properties and reservoir monitoring, and well testing, simulation, and predicting reservoir performance. The objectives, technical approach, and project status of each project are presented. The background, research results, and future plans for each project are discussed. The names, addresses, and telephone and telefax numbers are given for the DOE program manager and the principal investigators. (MHR)

  20. Comparing theories' performance in predicting violence.

    Science.gov (United States)

    Haas, Henriette; Cusson, Maurice

    2015-01-01

    The stakes of choosing the best theory as a basis for violence prevention and offender rehabilitation are high. However, no single theory of violence has ever been universally accepted by a majority of established researchers. Psychiatry, psychology and sociology are each subdivided into different schools relying upon different premises. All theories can produce empirical evidence for their validity, some of them stating the opposite of each other. Calculating different models with multivariate logistic regression on a dataset of N = 21,312 observations and ninety-two influences allowed a direct comparison of the performance of operationalizations of some of the most important schools. The psychopathology model ranked as the best model in terms of predicting violence right after the comprehensive interdisciplinary model. Next came the rational choice and lifestyle model and third the differential association and learning theory model. Other models namely the control theory model, the childhood-trauma model and the social conflict and reaction model turned out to have low sensitivities for predicting violence. Nevertheless, all models produced acceptable results in predictions of a non-violent outcome. Copyright © 2015. Published by Elsevier Ltd.

  1. Axisymmetric thrust-vectoring nozzle performance prediction

    International Nuclear Information System (INIS)

    Wilson, E. A.; Adler, D.; Bar-Yoseph, P.Z

    1998-01-01

    Throat-hinged geometrically variable converging-diverging thrust-vectoring nozzles directly affect the jet flow geometry and rotation angle at the nozzle exit as a function of the nozzle geometry, the nozzle pressure ratio and flight velocity. The consideration of nozzle divergence in the effective-geometric nozzle relation is theoretically considered here for the first time. In this study, an explicit calculation procedure is presented as a function of nozzle geometry at constant nozzle pressure ratio, zero velocity and altitude, and compared with experimental results in a civil thrust-vectoring scenario. This procedure may be used in dynamic thrust-vectoring nozzle design performance predictions or analysis for civil and military nozzles as well as in the definition of initial jet flow conditions in future numerical VSTOL/TV jet performance studies

  2. A Combined Thermodynamic and Kinetic Model for Barite Prediction at Oil Reservoir Conditions

    DEFF Research Database (Denmark)

    Zhen Wu, Bi Yun

    of the literature (PhD Study 1). The reviewed dataset was used as starting point for geochemical speciation modelling and applied to predict the stability of sulphate minerals in North Sea oil field brines. Second, for modelling of high salinity solutions using the Pitzer ion interaction approach, the temperature...... observations. This information can help planning mitigation and optimise costs in oil production....

  3. Prediction of sand production onset in petroleum reservoirs using a reliable classification approach

    Directory of Open Access Journals (Sweden)

    Farhad Gharagheizi

    2017-06-01

    It is shown that the developed model can accurately predict the sand production in a real field. The results of this study indicates that implementation of LSSVM modeling can effectively help completion designers to make an on time sand control plan with least deterioration of production.

  4. Transport of reservoir fines

    DEFF Research Database (Denmark)

    Yuan, Hao; Shapiro, Alexander; Stenby, Erling Halfdan

    Modeling transport of reservoir fines is of great importance for evaluating the damage of production wells and infectivity decline. The conventional methodology accounts for neither the formation heterogeneity around the wells nor the reservoir fines’ heterogeneity. We have developed an integral...... dispersion equation in modeling the transport and the deposition of reservoir fines. It successfully predicts the unsymmetrical concentration profiles and the hyperexponential deposition in experiments....

  5. Predicting permeability of low enthalpy geothermal reservoirs: A case study from the Upper Triassic − Lower Jurassic Gassum Formation, Norwegian–Danish Basin

    DEFF Research Database (Denmark)

    Weibel, Rikke; Olivarius, Mette; Kristensen, Lars

    2017-01-01

    This paper aims at improving the predictability of permeability in low enthalpy geothermal reser-voirs by investigating the effect of diagenesis on sandstone permeability. Applying the best fittedporosity–permeability trend lines, obtained from conventional core analysis, to log-interpreted poros...

  6. Feasibility of a data-constrained prediction of hydrocarbon reservoir sandstone microstructures

    International Nuclear Information System (INIS)

    Yang, Y S; Gureyev, T E; Tulloh, A; Clennell, M B; Pervukhina, M

    2010-01-01

    Microstructures are critical for defining material characteristics such as permeability, mechanical, electrical and other physical properties. However, the available techniques for determining compositional microstructures through segmentation of x-ray computed tomography (CT) images are inadequate when there are finer structures than the CT spatial resolution, i.e. when there is more than one material in each voxel. This is the case for CT imaging of geomaterials characterized with submicron porosity and clay coating that control petrophysical properties of rock. This note outlines our data-constrained modelling (DCM) approach for prediction of compositional microstructures, and our investigation of the feasibility of determining sandstone microstructures using multiple CT data sets with different x-ray beam energies. In the DCM approach, each voxel is assumed to contain a mixture of multiple materials, optionally including voids. Our preliminary comparisons using model samples indicate that the DCM-predicted compositional microstructure is consistent with the known original microstructure under low noise conditions. The approach is quite generic and is applicable to predictions of microstructure of various materials. (technical design note)

  7. Predicting Expressive Dynamics in Piano Performances using Neural Networks

    NARCIS (Netherlands)

    van Herwaarden, Sam; Grachten, Maarten; de Haas, W. Bas

    2014-01-01

    This paper presents a model for predicting expressive accentuation in piano performances with neural networks. Using Restricted Boltzmann Machines (RBMs), features are learned from performance data, after which these features are used to predict performed loudness. During feature learning, data

  8. A priori data-driven multi-clustered reservoir generation algorithm for echo state network.

    Directory of Open Access Journals (Sweden)

    Xiumin Li

    Full Text Available Echo state networks (ESNs with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in reservoir generation. This study focuses on the reservoir generation problem when ESN is used in environments with sufficient priori data available. Accordingly, a priori data-driven multi-cluster reservoir generation algorithm is proposed. The priori data in the proposed algorithm are used to evaluate reservoirs by calculating the precision and standard deviation of ESNs. The reservoirs are produced using the clustering method; only the reservoir with a better evaluation performance takes the place of a previous one. The final reservoir is obtained when its evaluation score reaches the preset requirement. The prediction experiment results obtained using the Mackey-Glass chaotic time series show that the proposed reservoir generation algorithm provides ESNs with extra prediction precision and increases the structure complexity of the network. Further experiments also reveal the appropriate values of the number of clusters and time window size to obtain optimal performance. The information entropy of the reservoir reaches the maximum when ESN gains the greatest precision.

  9. Predicting the Performance of Organic Corrosion Inhibitors

    Directory of Open Access Journals (Sweden)

    David A. Winkler

    2017-12-01

    Full Text Available The withdrawal of effective but toxic corrosion inhibitors has provided an impetus for the discovery of new, benign organic compounds to fill that role. Concurrently, developments in the high-throughput synthesis of organic compounds, the establishment of large libraries of available chemicals, accelerated corrosion inhibition testing technologies, and the increased capability of machine learning methods have made discovery of new corrosion inhibitors much faster and cheaper than it used to be. We summarize these technical developments in the corrosion inhibition field and describe how data-driven machine learning methods can generate models linking molecular properties to corrosion inhibition that can be used to predict the performance of materials not yet synthesized or tested. We briefly summarize the literature on quantitative structure–property relationships models of small organic molecule corrosion inhibitors. The success of these models provides a paradigm for rapid discovery of novel, effective corrosion inhibitors for a range of metals and alloys in diverse environments.

  10. Implications of changing water cycle for the performance and yield characteristics of the multi-purpose Beas Reservoir in India

    Science.gov (United States)

    Adeloye, A. J.; Ojha, C. S.; Soundharajan, B.; Remesan, R.

    2013-12-01

    There is considerable change in both the spatial and temporal patterns of monsoon rainfall in India, with implications for water resources availability and security. 'Mitigating the Impacts of Climate Change on India Agriculture' (MICCI) is one of five on-going scientific efforts being sponsored as part of the UK-NERC/India-MOES Changing Water Cycle (South Asia) initiative to further the understanding of the problem and proffer solutions that are robust and effective. This paper focuses on assessing the implications of projected climate change on the yield and performance characteristics of the Pong Reservoir on the Beas River, Himachal Pradesh, India. The Pong serves both hydropower and irrigation needs and is therefore strategic for the socio-economic well-being of the region as well as sustaining the livelihoods of millions of farmers that rely on it for irrigation. Simulated baseline and climate-change perturbed hydro-climate scenarios developed as part of a companion Work Package of MICCI formed the basis of the analysis. For both of these scenarios, reservoir analyses were carried out using the Sequent Peak Algorithm (SPA) and Pong's existing level of releases to derive rule curves for the reservoir. These rule curves then formed the basis of further reservoir behaviour simulations in WEAP and the resulting performance of the reservoir was summarised in terms of reliability, resilience, vulnerability and sustainability. The whole exercise was implemented within a Monte Carlo framework for the benefit of characterising the variability in the assessments. The results show that the rule curves developed using future hydro-climate are significantly changed from the baseline in that higher storages will be required to be maintained in the Pong in the future to achieve reliable performance. As far as the overall performance of the reservoir is concerned, future reliability (both time-based and volume-based) is not significantly different from the baseline, provided

  11. In vitro and in vivo percutaneous absorption of retinol from cosmetic formulations: Significance of the skin reservoir and prediction of systemic absorption

    International Nuclear Information System (INIS)

    Yourick, Jeffrey J.; Jung, Connie T.; Bronaugh, Robert L.

    2008-01-01

    The percutaneous absorption of retinol (Vitamin A) from cosmetic formulations was studied to predict systemic absorption and to understand the significance of the skin reservoir in in vitro absorption studies. Viable skin from fuzzy rat or human subjects was assembled in flow-through diffusion cells for in vitro absorption studies. In vivo absorption studies using fuzzy rats were performed in glass metabolism cages for collection of urine, feces, and body content. Retinol (0.3%) formulations (hydroalcoholic gel and oil-in-water emulsion) containing 3 H-retinol were applied and absorption was measured at 24 or 72 h. All percentages reported are % of applied dose. In vitro studies using human skin and the gel and emulsion vehicles found 0.3 and 1.3% retinol, respectively, in receptor fluid at 24 h. Levels of absorption in the receptor fluid increased over 72 h with the gel and emulsion vehicles. Using the gel vehicle, in vitro rat skin studies found 23% in skin and 6% in receptor fluid at 24 h, while 72-h studies found 18% in skin and 13% in receptor fluid. Thus, significant amounts of retinol remained in rat skin at 24 h and decreased over 72 h, with proportional increases in receptor fluid. In vivo rat studies with the gel found 4% systemic absorption of retinol after 24 h and systemic absorption did not increase at 72 h. Retinol remaining in rat skin after in vivo application was 18% and 13% of the applied dermal dose after 24 and 72 h, respectively. Similar observations were made with the oil-in water emulsion vehicle in the rat. Retinol formed a reservoir in rat skin both in vivo and in vitro. Little additional retinol was bioavailable after 24 h. Comparison of these in vitro and in vivo results for absorption through rat skin indicates that the 24-h in vitro receptor fluid value accurately estimated 24-h in vivo systemic absorption. Therefore, the best single estimate of retinol systemic absorption from in vitro human skin studies is the 24-h receptor fluid

  12. Study of ionically modified water performance in carbonate reservoir system by multivariate data analysis

    DEFF Research Database (Denmark)

    Sohal, Muhammad Adeel Nassar; Kucheryavskiy, Sergey V.; Thyne, Geoffrey

    2017-01-01

    the critical mechanisms at the pore scale. Better pore scale physico-chemical understanding will guide to formulate accurate reservoir-scale models. This paper presents a comprehensive meta-analysis of the proposed mechanisms using multivariate data analysis. Detailed review of the subject, including...... mechanisms with supporting and contradictory evidence has been presented by Sohal et al. (2016). In this study, the significance of each contributing factor to EOR was quantified and subjected to rigorous multivariate statistical analysis. The analysis was limited because there is no uniform methodology...

  13. DEVELOPMENT OF RESERVOIR CHARACTERIZATION TECHNIQUES AND PRODUCTION MODELS FOR EXPLOITING NATURALLY FRACTURED RESERVOIRS

    Energy Technology Data Exchange (ETDEWEB)

    Michael L. Wiggins; Raymon L. Brown; Faruk Civan; Richard G. Hughes

    2002-12-31

    For many years, geoscientists and engineers have undertaken research to characterize naturally fractured reservoirs. Geoscientists have focused on understanding the process of fracturing and the subsequent measurement and description of fracture characteristics. Engineers have concentrated on the fluid flow behavior in the fracture-porous media system and the development of models to predict the hydrocarbon production from these complex systems. This research attempts to integrate these two complementary views to develop a quantitative reservoir characterization methodology and flow performance model for naturally fractured reservoirs. The research has focused on estimating naturally fractured reservoir properties from seismic data, predicting fracture characteristics from well logs, and developing a naturally fractured reservoir simulator. It is important to develop techniques that can be applied to estimate the important parameters in predicting the performance of naturally fractured reservoirs. This project proposes a method to relate seismic properties to the elastic compliance and permeability of the reservoir based upon a sugar cube model. In addition, methods are presented to use conventional well logs to estimate localized fracture information for reservoir characterization purposes. The ability to estimate fracture information from conventional well logs is very important in older wells where data are often limited. Finally, a desktop naturally fractured reservoir simulator has been developed for the purpose of predicting the performance of these complex reservoirs. The simulator incorporates vertical and horizontal wellbore models, methods to handle matrix to fracture fluid transfer, and fracture permeability tensors. This research project has developed methods to characterize and study the performance of naturally fractured reservoirs that integrate geoscience and engineering data. This is an important step in developing exploitation strategies for

  14. Impacts of Spatial Climatic Representation on Hydrological Model Calibration and Prediction Uncertainty: A Mountainous Catchment of Three Gorges Reservoir Region, China

    Directory of Open Access Journals (Sweden)

    Yan Li

    2016-02-01

    Full Text Available Sparse climatic observations represent a major challenge for hydrological modeling of mountain catchments with implications for decision-making in water resources management. Employing elevation bands in the Soil and Water Assessment Tool-Sequential Uncertainty Fitting (SWAT2012-SUFI2 model enabled representation of precipitation and temperature variation with altitude in the Daning river catchment (Three Gorges Reservoir Region, China where meteorological inputs are limited in spatial extent and are derived from observations from relatively low lying locations. Inclusion of elevation bands produced better model performance for 1987–1993 with the Nash–Sutcliffe efficiency (NSE increasing by at least 0.11 prior to calibration. During calibration prediction uncertainty was greatly reduced. With similar R-factors from the earlier calibration iterations, a further 11% of observations were included within the 95% prediction uncertainty (95PPU compared to the model without elevation bands. For behavioral simulations defined in SWAT calibration using a NSE threshold of 0.3, an additional 3.9% of observations were within the 95PPU while the uncertainty reduced by 7.6% in the model with elevation bands. The calibrated model with elevation bands reproduced observed river discharges with the performance in the calibration period changing to “very good” from “poor” without elevation bands. The output uncertainty of calibrated model with elevation bands was satisfactory, having 85% of flow observations included within the 95PPU. These results clearly demonstrate the requirement to account for orographic effects on precipitation and temperature in hydrological models of mountainous catchments.

  15. Production Characteristics and Reservoir Quality at the Ivanić Oil Field (Croatia) Predicted by Machine Learning System

    OpenAIRE

    Hernitz, Zvonimir; Đureković, Miro; Crnički, Josip

    1996-01-01

    At the Ivanić oil field, hydrocarbons are accumulated in fine tomedium grained litharenits of the Ivanić-Grad Formation (Iva-sandstones member) of Upper Miocene age. Reservoir rocks are dividedinlo eight depositional (production) units (i1- i8). Deposits of eachunit are characterized by their own reservoir quality parameters(porosity, horizontal permeability, net pay ... ). Production characteristicsof 30 wells have been studied by a simple slatistical method. Twomajor production well ca...

  16. Pavement Performance : Approaches Using Predictive Analytics

    Science.gov (United States)

    2018-03-23

    Acceptable pavement condition is paramount to road safety. Using predictive analytics techniques, this project attempted to develop models that provide an assessment of pavement condition based on an array of indictors that include pavement distress,...

  17. Long-Term Performance of the Laguna de Barlovento Reservoir Water-Proofing using a PVC-P Geo membrane

    International Nuclear Information System (INIS)

    Blanco Fernandez, M.; Leiro Lopez, A.; Soriano Carrillo, J.; Crespo Mucientes, M.; Zornberg, J.; Aguilar Gonzalez, E.; Rico Arnaiz, G.; Pargada Iglesias, L.

    2014-01-01

    The Laguna de Barlovento reservoir was one of the most important European hydraulic projects at the time of its construction because of its high capacity and challenging location. At the time, the designers decided to waterproof this reservoirs with a geo membrane of plasticized polyvinyl chloride (PVC-P). This paper documents the initial characteristics of the geo membrane and its performance since its installation until 2010. The material characterization includes a comprehensive testing program, the results of which are presented. They include quantification of the geo membrane thickness, amount and nature of plasticizers, tensile properties, fold ability under low temperatures, dynamic impact resistance, puncture resistance, welding strength (both in the manufacturing facility and in the field), as well as the use of techniques involving optical and scanning electron microscopy. In addition, advanced analytical techniques, such as Fourier Transform Infrared Spectroscopy (FTIR), Gas Chromatography (GC) and Mass spectrometry (MS), were used in order to identify the plasticizers used in the geo membrane formulation. Fold ability tests were found to provide early indication of degradation. Results from reflection optical and electron scanning microscopy showed that, after 19 nineteen years of installation, the geo membrane remains in good conditions, particularly on the non-exposed side. (Author)

  18. Numerical Simulation Study on Steam-Assisted Gravity Drainage Performance in a Heavy Oil Reservoir with a Bottom Water Zone

    Directory of Open Access Journals (Sweden)

    Jun Ni

    2017-12-01

    Full Text Available In the Pikes Peak oil field near Lloydminster, Canada, a significant amount of heavy oil reserves is located in reservoirs with a bottom water zone. The properties of the bottom water zone and the operation parameters significantly affect oil production performance via the steam-assisted gravity drainage (SAGD process. Thus, in order to develop this type of heavy oil resource, a full understanding of the effects of these properties is necessary. In this study, the numerical simulation approach was applied to study the effects of properties in the bottom water zone in the SAGD process, such as the initial gas oil ratio, the thickness of the reservoir, and oil saturation of the bottom water zone. In addition, some operation parameters were studied including the injection pressure, the SAGD well pair location, and five different well patterns: (1 two corner wells, (2 triple wells, (3 downhole water sink well, (4 vertical injectors with a horizontal producer, and (5 fishbone well. The numerical simulation results suggest that the properties of the bottom water zone affect production performance extremely. First, both positive and negative effects were observed when solution gas exists in the heavy oil. Second, a logarithmical relationship was investigated between the bottom water production ratio and the thickness of the bottom water zone. Third, a non-linear relation was obtained between the oil recovery factor and oil saturation in the bottom water zone, and a peak oil recovery was achieved at the oil saturation rate of 30% in the bottom water zone. Furthermore, the operation parameters affected the heavy oil production performance. Comparison of the well patterns showed that the two corner wells and the triple wells patterns obtained the highest oil recovery factors of 74.71% and 77.19%, respectively, which are almost twice the oil recovery factors gained in the conventional SAGD process (47.84%. This indicates that the optimized SAGD process

  19. The Performance of Surfactant-Polymer Flooding in Horizontal Wells Consisting of Multilayers in a Reservoir System

    Directory of Open Access Journals (Sweden)

    Si Le Van

    2016-03-01

    Full Text Available Surfactant-polymer (SP flooding has been demonstrated to be an effective method to recover oil in the enhanced oil recovery (EOR stage when water flooding is no longer relevant. Theoretically, adding surfactant causes the reduction of the interfacial tension between oil and water in pores, therefore reducing the residual oil saturation, whereas the sweep efficiency will be significantly improved by the polymer injection as a result of proper mobility control. With regard to the well patterns, water flooding has demonstrated a high productivity in horizontal wells. Recently, other EOR processes have been increasingly applied to the horizontal wells in various well patterns. In this study, the efficiency of SP flooding applied to horizontal wells in various well configurations is investigated in order to select the best EOR performance in terms of either a technical or economical point of view. Furthermore, the reservoir is assumed to be anisotropic with four different layers that have same porosity but different permeability between each layer. The study figures out that, the utilization of a horizontal injector and producer always gives a higher oil production in comparison with the reference case of a conventional vertical injector and producer; however, the best EOR performances that demonstrate the higher oil recovery and lower fluid injected volume than those of the reference case are achieved when the production well is located in bottom layers and parallel with the injection well at a distance. While the location of producer decides oil productivity, the location of injector yet affects the uniformity of fluids propagation in the reservoir. A predefined feasibility factor is also taken into consideration in order to reject the infeasible cases that might give a high oil production but require a higher injected volume than the reference case. This factor is used as an economic parameter to evaluate the success of the EOR performance. The

  20. Growth performance and biochemical composition of nineteen microalgae collected from different Moroccan reservoirs

    Directory of Open Access Journals (Sweden)

    EL. A. IDRISSI ABDELKHALEK

    2016-03-01

    Full Text Available Macro- and microalgae have recently received much attention due to their valuable chemical constituents. In order to increase existing data, the authors studied nineteen microalgae species isolated from different reservoirs in the Fez region (northern Morocco, undertaking experiments to determine for each species the specific growth rate, their total amounts of proteins, carbohydrates and lipids and the influence of the growth phase on these chemical constituents. Conditions of cultivation were as follows: light intensity equal to 300 μmol photons m-2 s-1, with a temperature regime of 25/20°C (day/night and a 16/8 (light/dark photoperiod cycle. The growth rates of the nineteen studied species of microalgae showed a wide variation between species, ranging from 0.27 g l-1 d-1 for Chlamydomonas ovalis to 3.64 g l-1 d-1 for Chlorococcum wemmeri. Protein, carbohydrate and lipid contents varied greatly between taxa and within genera. Ankistrodesmus falcatus, Chlamydomonas ovalis, Chlorococcum sp., Hyaloraphidium contortum, Scenedesmus protuberans, and Synechocystis aquatilis tended to synthesize proteins, the concentrations exceeding 20% dry weight (DW. Ankistrodesmus falcatus, Ankistrodesmus sp., Chlorococcum wemmeri, Coenocystis sp., Isocystis sp., Lyngbya bergei, Oscillatoria amphibia, Polytoma papillatum, Scenedesmus protuberans, Scenedesmus sp. and Synechocystis aquatilis showed a high capacity for lipid storage, greater than 20% DW. For carbohydrate contents, only Scenedesmus protuberans and Scenedesmus quadricauda showed an excessive level compared to other scanned species with 29.21% and 24.76% DW, respectively.

  1. Evaluation of polyacrylamide gels with accelerator ammonium salts for water shutoff in ultralow temperature reservoirs: Gelation performance and application recommendations

    Directory of Open Access Journals (Sweden)

    Hu Jia

    2016-03-01

    Full Text Available Water shutoff in ultralow temperature reservoirs has received great attention in recent years. In previous study, we reported a phenol-formaldehyde-based gel formula with ammonium salt which can provide a gelation time between 2 hrs and 2 days at 25 °C. However, systematic evaluation and field recommendations of this gel formula when encountering complex reservoirs environment are not addressed. In this paper, how and why such practical considerations as water composition, temperature, pH, weight ratio of formaldehyde to resorcinol and contaminant Fe3+ to affect the gelation performance are examined. Brookfield DV-III and scanning electron microscopy (SEM are employed respectively for viscosity measurement and microstructure analysis. SEM results further illustrate the mechanism of the effect of salinity on gelation performance. It reveals that crosslinking done by covalent bond has great advantage for gel stability under high salinity environment. The target gel formula can provide desirable gelation time below 60 °C, perfect for 15–45 °C, while it is unfeasible to use high salinity to delay gelation at 60 °C. We summarized the effect of salinity on gelation performance of different gel formulas from the present study and published literature. The summarized data can provide important guideline for gel formula design before conducting any kinds of experiments. The variation of gelation performance at different salinity may be dominated by the interaction between crosslinker-salt-polymer, not only limited to “charge-screening effect” and “ion association” proposed by several authors. We hope the analysis encouraging further investigations. Some recommendations for field application of this gel are given in the end of this paper.

  2. Stochastic Prediction of Ventilation System Performance

    DEFF Research Database (Denmark)

    Haghighat, F.; Brohus, Henrik; Frier, Christian

    The paper briefly reviews the existing techniques for predicting the airflow rate due to the random nature of forcing functions, e.g. wind speed. The effort is to establish the relationship between the statistics of the output of a system and the statistics of the random input variables and param......The paper briefly reviews the existing techniques for predicting the airflow rate due to the random nature of forcing functions, e.g. wind speed. The effort is to establish the relationship between the statistics of the output of a system and the statistics of the random input variables...

  3. System Predicts Critical Runway Performance Parameters

    Science.gov (United States)

    Millen, Ernest W.; Person, Lee H., Jr.

    1990-01-01

    Runway-navigation-monitor (RNM) and critical-distances-process electronic equipment designed to provide pilot with timely and reliable predictive navigation information relating to takeoff, landing and runway-turnoff operations. Enables pilot to make critical decisions about runway maneuvers with high confidence during emergencies. Utilizes ground-referenced position data only to drive purely navigational monitor system independent of statuses of systems in aircraft.

  4. Predicting spread of invasive exotic plants into de-watered reservoirs following dam removal on the Elwha River, Olympic National Park, Washington

    Science.gov (United States)

    Woodward, Andrea; Torgersen, Christian E.; Chenoweth, Joshua; Beirne, Katherine; Acker, Steve

    2011-01-01

    The National Park Service is planning to start the restoration of the Elwha River ecosystem in Olympic National Park by removing two high head dams beginning in 2011. The potential for dispersal of exotic plants into dewatered reservoirs following dam removal, which would inhibit restoration of native vegetation, is of great concern. We focused on predicting long-distance dispersal of invasive exotic plants rather than diffusive spread because local sources of invasive species have been surveyed. We included the long-distance dispersal vectors: wind, water, birds, beavers, ungulates, and users of roads and trails. Using information about the current distribution of invasive species from two surveys, various geographic information system techniques and models, and statistical methods, we identified high-priority areas for Park staff to treat prior to dam removal, and areas of the dewatered reservoirs at risk after dam removal.

  5. Surrogate reservoir models for CSI well probabilistic production forecast

    Directory of Open Access Journals (Sweden)

    Saúl Buitrago

    2017-09-01

    Full Text Available The aim of this work is to present the construction and use of Surrogate Reservoir Models capable of accurately predicting cumulative oil production for every well stimulated with cyclic steam injection at any given time in a heavy oil reservoir in Mexico considering uncertain variables. The central composite experimental design technique was selected to capture the maximum amount of information from the model response with a minimum number of reservoir models simulations. Four input uncertain variables (the dead oil viscosity with temperature, the reservoir pressure, the reservoir permeability and oil sand thickness hydraulically connected to the well were selected as the ones with more impact on the initial hot oil production rate according to an analytical production prediction model. Twenty five runs were designed and performed with the STARS simulator for each well type on the reservoir model. The results show that the use of Surrogate Reservoir Models is a fast viable alternative to perform probabilistic production forecasting of the reservoir.

  6. Reservoir management

    International Nuclear Information System (INIS)

    Satter, A.; Varnon, J.E.; Hoang, M.T.

    1992-01-01

    A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neural reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers, geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

  7. Reservoir management

    International Nuclear Information System (INIS)

    Satter, A.; Varnon, J.E.; Hoang, M.T.

    1992-01-01

    A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neutral reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

  8. Performance samples on academic tasks : improving prediction of academic performance

    NARCIS (Netherlands)

    Tanilon, Jenny

    2011-01-01

    This thesis is about the development and validation of a performance-based test, labeled as Performance Samples on academic tasks in Education and Child Studies (PSEd). PSEd is designed to identify students who are most able to perform the academic tasks involved in an Education and Child Studies

  9. Performance analysis and prediction in triathlon.

    Science.gov (United States)

    Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

    2016-01-01

    Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

  10. Predicting Students' Performance in the Senior Secondary ...

    African Journals Online (AJOL)

    cce

    correlation design. ... the JSC examinations were a good predictor of performance at SSC ..... Table 12: Effects of the Independent Variables (JSCE 2000) on the .... JAMB Brochure, Abuja: Joint Admissions and Matriculation Examinations, 2-3.

  11. SYRUS: Understanding and Predicting Multitasking Performance

    National Research Council Canada - National Science Library

    Oswald, Frederick L; Hambrick, D. Z; Jones, L. A; Ghumman, Sonia S

    2007-01-01

    .... Fourth, related to the previous point, a summarization of our initial empirical work on multitasking, based on college-student participants who engaged in a computerized multitasking performance task...

  12. A two reservoir model to predict Escherichia coli losses to water from pastures grazed by dairy cows.

    Science.gov (United States)

    Muirhead, R W; Monaghan, R M

    2012-04-01

    Animal agriculture has been identified as an important source of diffuse faecal microbial pollution of water. Our current understanding of the losses of faecal microbes from grazed pasture systems is however poor. To help synthesise our current knowledge, a simple two reservoir model was constructed to represent the faecal and environmental sources of Escherichia coli found in a grazed pastoral system. The size of the faecal reservoir was modelled on a daily basis with inputs from grazing animals, and losses due to die-off of E. coli and decomposition of the faecal material. Estimates were made of transport coefficients of E. coli losses from the two reservoirs. The concentration of E. coli measured in overland flow and artificial drainage from grazed plots, used for calibration of the model, showed a significant (Ppasture systems. Research is needed to understand the behaviour and impact of this environmental reservoir. Scenario analysis using the model indicated that rather than manipulating the faecal material itself post defecation, mitigation options should focus on manipulating grazing management. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. A theoretical study on the performances of thermoelectric heat engine and refrigerator with two-dimensional electron reservoirs

    International Nuclear Information System (INIS)

    Luo, Xiaoguang; Long, Kailin; Wang, Jun; Qiu, Teng; He, Jizhou; Liu, Nian

    2014-01-01

    Theoretical thermoelectric nanophysics models of low-dimensional electronic heat engine and refrigerator devices, comprising two-dimensional hot and cold reservoirs and an interconnecting filtered electron transport mechanism have been established. The models were used to numerically simulate and evaluate the thermoelectric performance and energy conversion efficiencies of these low-dimensional devices, based on three different types of electron transport momentum-dependent filters, referred to herein as k x , k y , and k r filters. Assuming the Fermi-Dirac distribution of electrons, expressions for key thermoelectric performance parameters were derived for the resonant transport processes, in which the transmission of electrons has been approximated as a Lorentzian resonance function. Optimizations were carried out and the corresponding optimized design parameters have been determined, including but not limited to the universal theoretical upper bound of the efficiency at maximum power for heat engines, and the maximum coefficient of performance for refrigerators. From the results, it was determined that k r filter delivers the best thermoelectric performance, followed by the k x filter, and then the k y filter. For refrigerators with any one of three filters, an optimum range for the full width at half maximum of the transport resonance was found to be B T.

  14. Dichotic listening performance predicts language comprehension.

    Science.gov (United States)

    Asbjørnsen, Arve E; Helland, Turid

    2006-05-01

    Dichotic listening performance is considered a reliable and valid procedure for the assessment of language lateralisation in the brain. However, the documentation of a relationship between language functions and dichotic listening performance is sparse, although it is accepted that dichotic listening measures language perception. In particular, language comprehension should show close correspondence to perception of language stimuli. In the present study, we tested samples of reading-impaired and normally achieving children between 10 and 13 years of age with tests of reading skills, language comprehension, and dichotic listening to consonant-vowel (CV) syllables. A high correlation between the language scores and the dichotic listening performance was expected. However, since the left ear score is believed to be an error when assessing language laterality, covariation was expected for the right ear scores only. In addition, directing attention to one ear input was believed to reduce the influence of random factors, and thus show a more concise estimate of left hemisphere language capacity. Thus, a stronger correlation between language comprehension skills and the dichotic listening performance when attending to the right ear was expected. The analyses yielded a positive correlation between the right ear score in DL and language comprehension, an effect that was stronger when attending to the right ear. The present results confirm the assumption that dichotic listening with CV syllables measures an aspect of language perception and language skills that is related to general language comprehension.

  15. Challenges of student selection: Predicting academic performance ...

    African Journals Online (AJOL)

    Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the

  16. Goal Setting and Expectancy Theory Predictions of Effort and Performance.

    Science.gov (United States)

    Dossett, Dennis L.; Luce, Helen E.

    Neither expectancy (VIE) theory nor goal setting alone are effective determinants of individual effort and task performance. To test the combined ability of VIE and goal setting to predict effort and performance, 44 real estate agents and their managers completed questionnaires. Quarterly income goals predicted managers' ratings of agents' effort,…

  17. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  18. Predicting sales performance: Strengthening the personality – job performance linkage

    NARCIS (Netherlands)

    T.B. Sitser (Thomas)

    2014-01-01

    markdownabstract__Abstract__ Many organizations worldwide use personality measures to select applicants for sales jobs or to assess incumbent sales employees. In the present dissertation, consisting of four independent studies, five approaches to strengthen the personality-sales performance

  19. Real-Time Flood Control by Tree-Based Model Predictive Control Including Forecast Uncertainty: A Case Study Reservoir in Turkey

    Directory of Open Access Journals (Sweden)

    Gökçen Uysal

    2018-03-01

    Full Text Available Optimal control of reservoirs is a challenging task due to conflicting objectives, complex system structure, and uncertainties in the system. Real time control decisions suffer from streamflow forecast uncertainty. This study aims to use Probabilistic Streamflow Forecasts (PSFs having a lead-time up to 48 h as input for the recurrent reservoir operation problem. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC. Deterministic Streamflow Forecasts (DSFs are provided by applying random perturbations on perfect data. PSFs are synthetically generated from DSFs by a new approach which explicitly presents dynamic uncertainty evolution. We assessed different variables in the generation of stochasticity and compared the results using different scenarios. The developed real-time hourly flood control was applied to a test case which had limited reservoir storage and restricted downstream condition. According to hindcasting closed-loop experiment results, TB-MPC outperforms the deterministic counterpart in terms of decreased downstream flood risk according to different independent forecast scenarios. TB-MPC was also tested considering different number of tree branches, forecast horizons, and different inflow conditions. We conclude that using synthetic PSFs in TB-MPC can provide more robust solutions against forecast uncertainty by resolution of uncertainty in trees.

  20. High-performance modeling of CO2 sequestration by coupling reservoir simulation and molecular dynamics

    KAUST Repository

    Bao, Kai; Yan, Mi; Lu, Ligang; Allen, Rebecca; Salam, Amgad; Jordan, Kirk E.; Sun, Shuyu

    2013-01-01

    multicomponent compositional flow simulation to handle more complicated physical process in the future. Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our

  1. Fiscal 1997 report on the verification survey of geothermal exploration technology. 5-1. Development of the reservoir variation survey method (technology of prediction of reservoir variation); 1997 nendo chinetsu tansa gijutsu nado kensho chosa. Choryuso hendo tansaho kaihatsu (choryuso hendo yosoku gijutsu) hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    For the reservoir evaluation at an initial developmental stage and stabilization/maintenance of power after the start of operation, the fiscal 1997 result was described of the study of technology of prediction of reservoir variation. Using the conventional post processor, feasibilities were computed of reservoir models and behavior after the development, and gravity/self potential/resistivity variation. Variation in the seismic wave speed structure was large in travel time change distribution. The measuring accuracy of 1m sec is required to get enough detection resolving power. A conceptual design of the post processor development was conducted to study a system operated on Windows. Based on the reservoir numerical simulation technology, by taking in variation parameters such as gravity and self potentials as new model constraint conditions, the reservoir modeling technology which increased in accuracy by history matching was trially developed. Using the conventional reservoir model in the Oguni area, predictably computed were reservoir behaviors during 50 years which simulated a 20 MW development. Effectiveness of the post processor were able to be shown though influenced by characteristics such as permeability and resistivity. 74 refs., 95 refs., 12 tabs.

  2. Does IQ Really Predict Job Performance?

    Science.gov (United States)

    Richardson, Ken; Norgate, Sarah H.

    2015-01-01

    IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test validity, therefore, has always been indirect, by correlating individual differences in test scores with what are assumed to be other criteria of intelligence. Job performance has, for several reasons, been one such criterion. Correlations of around 0.5 have been regularly cited as evidence of test validity, and as justification for the use of the tests in developmental studies, in educational and occupational selection and in research programs on sources of individual differences. Here, those correlations are examined together with the quality of the original data and the many corrections needed to arrive at them. It is concluded that considerable caution needs to be exercised in citing such correlations for test validation purposes. PMID:26405429

  3. Numerical modeling capabilities to predict repository performance

    International Nuclear Information System (INIS)

    1979-09-01

    This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used

  4. Fortescue reservoir development and reservoir studies

    Energy Technology Data Exchange (ETDEWEB)

    Henzell, S.T.; Hicks, G.J.; Horden, M.J.; Irrgang, H.R.; Janssen, E.J.; Kable, C.W.; Mitchell, R.A.H.; Morrell, N.W.; Palmer, I.D.; Seage, N.W.

    1985-03-01

    The Fortescue field in the Gippsland Basin, offshore southeastern Australia is being developed from two platforms (Fortescue A and Cobia A) by Esso Australia Ltd. (operator) and BHP Petroleum. The Fortescue reservoir is a stratigraphic trap at the top of the Latrobe Group of sediments. It overlies the western flank of the Halibut and Cobia fields and is separated from them by a non-net sequence of shales and coals which form a hydraulic barrier between the two systems. Development drilling into the Fortescue reservoir commenced in April 1983 with production coming onstream in May 1983. Fortescue, with booked reserves of 44 stock tank gigalitres (280 million stock tank barrels) of 43/sup 0/ API oil, is the seventh major oil reservoir to be developed in the offshore Gippsland Basin by Esso/BHP. In mid-1984, after drilling a total of 20 exploration and development wells, and after approximately one year of production, a detailed three-dimensional, two-phase reservoir simulation study was performed to examine the recovery efficiency, drainage patterns, pressure performance and production rate potential of the reservoir. The model was validated by history matching an extensive suite of Repeat Formation Test (RFT) pressure data. The results confirmed the reserves basis, and demonstrated that the ultimate oil recovery from the reservoir is not sensitive to production rate. This result is consistent with studies on other high quality Latrobe Group reservoirs in the Gippsland Basin which contain undersaturated crudes and receive very strong water drive from the Basin-wide aquifer system. With the development of the simulation model during the development phase, it has been possible to more accurately define the optimal well pattern for the remainder of the development.

  5. Abiquiu Dam and Reservoir, Rio Grande Basin, Rio Chama, New Mexico. Embankment Criteria and Performance Report.

    Science.gov (United States)

    1987-04-01

    EMBANKMENT CRITERIA AND PERFORMANCE REPORT PERTINENT DATA 1. General Data. LOCATION: Rio Arriba County, New Mexico, on the Rio Chama at river mile 33. PURPOSE...is located across the Rio Chama, approximately 30 miles upstream from its confluence with the Rio Grande, in Rio Arriba County, New Mexico. The dam is...6600- 4 i ’. 6600 65060- -60 6600- a + v6500s-go FA**v~w -6500 6300- 60 - ~ ~ ~ wo Ala filll------------------ EMBNKEN SECTION62 *LDN WOR SAFEL VAIE

  6. Reliable predictions of waste performance in a geologic repository

    International Nuclear Information System (INIS)

    Pigford, T.H.; Chambre, P.L.

    1985-08-01

    Establishing reliable estimates of long-term performance of a waste repository requires emphasis upon valid theories to predict performance. Predicting rates that radionuclides are released from waste packages cannot rest upon empirical extrapolations of laboratory leach data. Reliable predictions can be based on simple bounding theoretical models, such as solubility-limited bulk-flow, if the assumed parameters are reliably known or defensibly conservative. Wherever possible, performance analysis should proceed beyond simple bounding calculations to obtain more realistic - and usually more favorable - estimates of expected performance. Desire for greater realism must be balanced against increasing uncertainties in prediction and loss of reliability. Theoretical predictions of release rate based on mass-transfer analysis are bounding and the theory can be verified. Postulated repository analogues to simulate laboratory leach experiments introduce arbitrary and fictitious repository parameters and are shown not to agree with well-established theory. 34 refs., 3 figs., 2 tabs

  7. Enhancing pavement performance prediction models for the Illinois Tollway System

    OpenAIRE

    Laxmikanth Premkumar; William R. Vavrik

    2016-01-01

    Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway) with over 2000 lane miles of pavement utilizes the condition rating survey (CRS) methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT) are used by th...

  8. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  9. Performance prediction method for a multi-stage Knudsen pump

    Science.gov (United States)

    Kugimoto, K.; Hirota, Y.; Kizaki, Y.; Yamaguchi, H.; Niimi, T.

    2017-12-01

    In this study, the novel method to predict the performance of a multi-stage Knudsen pump is proposed. The performance prediction method is carried out in two steps numerically with the assistance of a simple experimental result. In the first step, the performance of a single-stage Knudsen pump was measured experimentally under various pressure conditions, and the relationship of the mass flow rate was obtained with respect to the average pressure between the inlet and outlet of the pump and the pressure difference between them. In the second step, the performance of a multi-stage pump was analyzed by a one-dimensional model derived from the mass conservation law. The performances predicted by the 1D-model of 1-stage, 2-stage, 3-stage, and 4-stage pumps were validated by the experimental results for the corresponding number of stages. It was concluded that the proposed prediction method works properly.

  10. Reservoir management under geological uncertainty using fast model update

    NARCIS (Netherlands)

    Hanea, R.; Evensen, G.; Hustoft, L.; Ek, T.; Chitu, A.; Wilschut, F.

    2015-01-01

    Statoil is implementing "Fast Model Update (FMU)," an integrated and automated workflow for reservoir modeling and characterization. FMU connects all steps and disciplines from seismic depth conversion to prediction and reservoir management taking into account relevant reservoir uncertainty. FMU

  11. Hybrid Corporate Performance Prediction Model Considering Technical Capability

    Directory of Open Access Journals (Sweden)

    Joonhyuck Lee

    2016-07-01

    Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.

  12. Tailor-made surfactants for optimized chemical EOR. Meeting oil reservoir conditions by applied knowledge of structure-performance relationship in extended surfactants

    Energy Technology Data Exchange (ETDEWEB)

    Trahan, G.; Sorensen, W. [Sasol North America Inc., Westlake, LA (United States); Jakobs-Sauter, B. [Sasol Germany GmbH (Germany)

    2013-08-01

    Formulating the surfactant package for chemical EOR is a time consuming and expensive process - the formulation needs to fit the specific reservoir conditions (like oil type, temperature, salinity, etc.) to give optimum performance and the number of formulation variables is virtually endless. This paper studies the impact of surfactant structure on EOR formulation ability and performance and how to adjust the structure of the surfactant molecule to meet a specific reservoir's needs. Data from salinity phase boundary studies of alcohol propoxy sulfates illustrate how changes in alcohol structure as well as in propylene oxide level can shift optimum salinity and temperature to the desired range in a given model oil. From these data the impact of individual structural units was evaluated. Application of the HLD model (Hydrophilic-Lipophilic Deviation) shows how to extrapolate from the known data set to actual reservoir conditions. This is illustrated by studies on crude oil samples. Additional tests study how effective the selected surfactants perform. The HLD concept proves to be a valuable tool to select and tailor surfactants to individual reservoir needs, thus simplifying the surfactant screening process for EOR formulations by pre-selection of suitable structures and ultimately reducing cost and effort on the way to the most effective chemical EOR package. (orig.)

  13. Essays on predictability of emerging markets growth and financial performance

    OpenAIRE

    Banegas, Maria Ayelen

    2011-01-01

    This dissertation seeks to better understand the underlying factors driving financial performance and economic activity in international markets. The first chapter "Predictability of Growth in Emerging Markets: Information in Financial Aggregates" tests for predictability of output growth in a panel of twenty-two emerging market economies. I use pooled panel data methods that control for endogeneity and persistence in the predictor variables to test the predictive power of a large set of fina...

  14. Mastery and Performance Goals Predict Epistemic and Relational Conflict Regulation

    Science.gov (United States)

    Darnon, Celine; Muller, Dominique; Schrager, Sheree M.; Pannuzzo, Nelly; Butera, Fabrizio

    2006-01-01

    The present research examines whether mastery and performance goals predict different ways of reacting to a sociocognitive conflict with another person over materials to be learned, an issue not yet addressed by the achievement goal literature. Results from 2 studies showed that mastery goals predicted epistemic conflict regulation (a conflict…

  15. Comparison and Prediction of Preclinical Students' Performance in ...

    African Journals Online (AJOL)

    olayemitoyin

    The data support the hypothesis that students who performed well in one discipline were likely to .... predict success in the clinical curriculum (Baciewicz,. 1990). Similarly ... the International Association of Medical Science. Educators. 17-20.

  16. Determining Mean Predicted Performance for Army Job Families

    National Research Council Canada - National Science Library

    Zeidner, Joseph

    2003-01-01

    The present study is designed to obtain mean predicted performance (MPPs) for the 9- and 17-job families, using composites based on 7 ASVAB tests, using a triple cross validation design permitting completely unbiased estimates of MPP...

  17. Predictive factors for masticatory performance in Duchenne muscular dystrophy

    NARCIS (Netherlands)

    Bruggen, H.W. van; Engel-Hoek, L. van den; Steenks, M.H.; Bronkhorst, E.M.; Creugers, N.H.; Groot, I.J.M. de; Kalaykova, S.

    2014-01-01

    Patients with Duchenne muscular dystrophy (DMD) report masticatory and swallowing problems. Such problems may cause complications such as choking, and feeling of food sticking in the throat. We investigated whether masticatory performance in DMD is objectively impaired, and explored predictive

  18. Time-Lapse Seismic Monitoring and Performance Assessment of CO2 Sequestration in Hydrocarbon Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Datta-Gupta, Akhil [Texas Engineering Experiment Station, College Station, TX (United States)

    2017-06-15

    Carbon dioxide sequestration remains an important and challenging research topic as a potentially viable approach for mitigating the effects of greenhouse gases on global warming (e.g., Chu and Majumdar, 2012; Bryant, 2007; Orr, 2004; Hepple and Benson, 2005; Bachu, 2003; Grimston et al., 2001). While CO2 can be sequestered in oceanic or terrestrial biomass, the most mature and effective technology currently available is sequestration in geologic formations, especially in known hydrocarbon reservoirs (Barrufet et al., 2010; Hepple and Benson, 2005). However, challenges in the design and implementation of sequestration projects remain, especially over long time scales. One problem is that the tendency for gravity override caused by the low density and viscosity of CO2. In the presence of subsurface heterogeneity, fractures and faults, there is a significant risk of CO2 leakage from the sequestration site into overlying rock compared to other liquid wastes (Hesse and Woods, 2010; Ennis-King and Patterson, 2002; Tsang et al., 2002). Furthermore, the CO2 will likely interact chemically with the rock in which it is stored, so that understanding and predicting its transport behavior during sequestration can be complex and difficult (Mandalaparty et al., 2011; Pruess et al., 2003). Leakage of CO2 can lead to such problems as acidification of ground water and killing of plant life, in addition to contamination of the atmosphere (Ha-Duong, 2003; Gasda et al., 2004). The development of adequate policies and regulatory systems to govern sequestration therefore requires improved characterization of the media in which CO2 is stored and the development of advanced methods for detecting and monitoring its flow and transport in the subsurface (Bachu, 2003).

  19. Application of probabilistic facies prediction and estimation of rock physics parameters in a carbonate reservoir from Iran

    International Nuclear Information System (INIS)

    Karimpouli, Sadegh; Hassani, Hossein; Nabi-Bidhendi, Majid; Khoshdel, Hossein; Malehmir, Alireza

    2013-01-01

    In this study, a carbonate field from Iran was studied. Estimation of rock properties such as porosity and permeability is much more challenging in carbonate rocks than sandstone rocks because of their strong heterogeneity. The frame flexibility factor (γ) is a rock physics parameter which is related not only to pore structure variation but also to solid/pore connectivity and rock texture in carbonate reservoirs. We used porosity, frame flexibility factor and bulk modulus of fluid as the proper parameters to study this gas carbonate reservoir. According to rock physics parameters, three facies were defined: favourable and unfavourable facies and then a transition facies located between these two end members. To capture both the inversion solution and associated uncertainty, a complete implementation of the Bayesian inversion of the facies from pre-stack seismic data was applied to well data and validated with data from another well. Finally, this method was applied on a 2D seismic section and, in addition to inversion of petrophysical parameters, the high probability distribution of favorable facies was also obtained. (paper)

  20. Predictive testing of performance of metals in HTR service environments

    International Nuclear Information System (INIS)

    Kondo, T.; Shindo, M.; Tamura, M.; Tsuji, H.; Kurata, Y.; Tsukada, T.

    1982-01-01

    Status of the material testing in simulated HTGR environment is reviewed with special attention focused on the methodology of the prediction of performance in long time. Importance of controlling effective chemical potentials relations in the material-environmental interface is stressed in regard of the complex inter-dependent kinetic relation between oxidation and carbon transport. Based on the recent experimental observations, proposals are made to establish some procedures for conservative prediction of the metal performance

  1. Prediction of Job Performance: Review of Military Studies

    Science.gov (United States)

    1982-03-01

    an assessment center to predict filed leadership performance of Army officers and NCOs. Proceedings of the 19th Annual Military Testing Association...C. Behaviors, results, and organizational effectiveness: The problem of criteria. In Dunnette, M. D. (Ed.), Handbook of Industrial and organizatin ...than for the Navy enlisted group. 30. Dyer, F. N., & Hlilligoss, R. Z. Using an assessment center to predict field leadership performance of Army

  2. Measuring and Predicting Sleep and Performance During Military Operations

    Science.gov (United States)

    2012-08-23

    strengths of this modeling approach is that accurate predictions of fatigue, performance, or alert- ness can be made from observed sleep timing...and, in which fatigue, performance, or alertness predictions are required prior to the task. Limitations of Current Models The strengths and...mean ± SD, 35.9 ± 1.2 hours), crews flew to Auckland , New Zealand, where another short layover was un- dertaken (23.6 ± 0.95 hours). A final flight

  3. Performance Prediction of Constrained Waveform Design for Adaptive Radar

    Science.gov (United States)

    2016-11-01

    the famous Woodward quote, having a ubiquitous feeling for all radar waveform design (and performance prediction) researchers , that is found at the end...discuss research that develops performance prediction models to quantify the impact on SINR when an amplitude constraint is placed on a radar waveform...optimize the radar perfor- mance for the particular scenario and tasks. There have also been several survey papers on various topics in waveform design for

  4. Multivariate performance reliability prediction in real-time

    International Nuclear Information System (INIS)

    Lu, S.; Lu, H.; Kolarik, W.J.

    2001-01-01

    This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

  5. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  6. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  7. Predicting the downstream impact of ensembles of small reservoirs with special reference to the Volta Basin, West Africa

    Science.gov (United States)

    van de Giesen, N.; Andreini, M.; Liebe, J.; Steenhuis, T.; Huber-Lee, A.

    2005-12-01

    After a strong reduction in investments in water infrastructure in Sub-Saharan Africa, we now see a revival and increased interest to start water-related projects. The global political willingness to work towards the UN millennium goals are an important driver behind this recent development. Large scale irrigation projects, such as were constructed at tremendous costs in the 1970's and early 1980's, are no longer seen as the way forward. Instead, the construction of a large number of small, village-level irrigation schemes is thought to be a more effective way to improve food production. Such small schemes would fit better in existing and functioning governance structures. An important question now becomes what the cumulative (downstream) impact is of a large number of small irrigation projects, especially when they threaten to deplete transboundary water resources. The Volta Basin in West Africa is a transboundary river catchment, divided over six countries. Of these six countries, upstream Burkina Faso and downstream Ghana are the most important and cover 43% and 42% of the basin, respectively. In Burkina Faso (and also North Ghana), small reservoirs and associated irrigation schemes are already an important means to improve the livelihoods of the rural population. In fact, over two thousand such schemes have already been constructed in Burkina Faso and further construction is to be expected in the light of the UN millennium goals. The cumulative impact of these schemes would affect the Akosombo Reservoir, one of the largest manmade lakes in the world and an important motor behind the economic development in (South) Ghana. This presentation will put forward an analytical framework that allows for the impact assessment of (large) ensembles of small reservoirs. It will be shown that despite their relatively low water use efficiencies, the overall impact remains low compared to the impact of large dams. The tools developed can be used in similar settings elsewhere

  8. Naturally fractured reservoirs-yet an unsolved mystery

    International Nuclear Information System (INIS)

    Zahoor, M.K.

    2013-01-01

    Some of the world's most profitable reservoirs are assumed to be naturally fractured reservoirs (NFR). Effective evaluation, prediction and planning of these reservoirs require an early recognition of the role of natural fractures and then a comprehensive study of factors which affect the flowing performance through these fractures is necessary. As NFRs are the combination of matrix and fractures mediums so their analysis varies from non-fractured reservoirs. Matrix acts as a storage medium while mostly fluid flow takes place from fracture network. Many authors adopted different approaches to understand the flow behavior in such reservoirs. In this paper a broad review about the previous work done in naturally fractured reservoirs area is outlined and a different idea is initiated for the NFR simulation studies. The role of capillary pressure in natural fractures is always been a key factor for accurate recovery estimations. Also recovery through these reservoirs is dependent upon grid block shape while doing NFR simulation. Some authors studied above mentioned factors in combination with other rock properties to understand the flow behavior in such reservoirs but less emphasis was given for checking the effects on recovery estimations by the variations of only fracture capillary pressures and grid block shapes. So there is need to analyze the behavior of NFR for the mentioned conditions. (author)

  9. Preconditioning methods to improve SAGD performance in heavy oil and bitumen reservoirs with variable oil phase viscosity

    Energy Technology Data Exchange (ETDEWEB)

    Gates, I.D. [Gushor Inc., Calgary, AB (Canada)]|[Calgary Univ., AB (Canada). Dept. of Chemical and Petroleum Engineering; Larter, S.R.; Adams, J.J.; Snowdon, L.; Jiang, C. [Gushor Inc., Calgary, AB (Canada)]|[Calgary Univ., Calgary, AB (Canada). Dept. of Geoscience

    2008-10-15

    This study investigated preconditioning techniques for altering reservoir fluid properties prior to steam assisted gravity drainage (SAGD) recovery processes. Viscosity-reducing agents were distributed in mobile reservoir water. Simulations were conducted to demonstrate the method's ability to modify oil viscosity prior to steam injection. The study simulated the action of water soluble organic solvents that preferentially partitioned in the oil phase. The solvent was injected with water into the reservoir in a slow waterflood that did not displace oil from the near wellbore region. A reservoir simulation model was used to investigate the technique. Shu's correlation was used to establish a viscosity correlation for the bitumen and solvent mixtures. Solvent injection was modelled by converting the oil phase viscosity through time. Over the first 2 years, oil rates of the preconditioned case were double that of the non-preconditioned case study. However, after 11 years, the preconditioned case's rates declined below rates observed in the non-preconditioned case. The model demonstrated that oil viscosity distributions were significantly altered using the preconditioners. The majority of the most viscous oil surrounding the production well was significantly reduced. It was concluded that accelerated steam chamber growth provided faster access to lower viscosity materials at the top of the reservoir. 12 refs., 9 figs.

  10. Predicting Document Retrieval System Performance: An Expected Precision Measure.

    Science.gov (United States)

    Losee, Robert M., Jr.

    1987-01-01

    Describes an expected precision (EP) measure designed to predict document retrieval performance. Highlights include decision theoretic models; precision and recall as measures of system performance; EP graphs; relevance feedback; and computing the retrieval status value of a document for two models, the Binary Independent Model and the Two Poisson…

  11. Predicting Academic Performance Based on Students' Blog and Microblog Posts

    NARCIS (Netherlands)

    Dascalu, Mihai; Popescu, Elvira; Becheru, Alexandru; Crossley, Scott; Trausan-Matu, Stefan

    2016-01-01

    This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in

  12. Static reservoir modeling of the Bahariya reservoirs for the oilfields development in South Umbarka area, Western Desert, Egypt

    Science.gov (United States)

    Abdel-Fattah, Mohamed I.; Metwalli, Farouk I.; Mesilhi, El Sayed I.

    2018-02-01

    3D static reservoir modeling of the Bahariya reservoirs using seismic and wells data can be a relevant part of an overall strategy for the oilfields development in South Umbarka area (Western Desert, Egypt). The seismic data is used to build the 3D grid, including fault sticks for the fault modeling, and horizon interpretations and surfaces for horizon modeling. The 3D grid is the digital representation of the structural geology of Bahariya Formation. When we got a reasonably accurate representation, we fill the 3D grid with facies and petrophysical properties to simulate it, to gain a more precise understanding of the reservoir properties behavior. Sequential Indicator Simulation (SIS) and Sequential Gaussian Simulation (SGS) techniques are the stochastic algorithms used to spatially distribute discrete reservoir properties (facies) and continuous reservoir properties (shale volume, porosity, and water saturation) respectively within the created 3D grid throughout property modeling. The structural model of Bahariya Formation exhibits the trapping mechanism which is a fault assisted anticlinal closure trending NW-SE. This major fault breaks the reservoirs into two major fault blocks (North Block and South Block). Petrophysical models classified Lower Bahariya reservoir as a moderate to good reservoir rather than Upper Bahariya reservoir in terms of facies, with good porosity and permeability, low water saturation, and moderate net to gross. The Original Oil In Place (OOIP) values of modeled Bahariya reservoirs show hydrocarbon accumulation in economic quantity, considering the high structural dips at the central part of South Umbarka area. The powerful of 3D static modeling technique has provided a considerable insight into the future prediction of Bahariya reservoirs performance and production behavior.

  13. Prediction of radionuclide migration in the Pripyat river and Dnieper reservoirs and decision support of water protection measures on the basis of mathematical modelling

    International Nuclear Information System (INIS)

    Morozov, A.A.; Zheleznyak, M.J.; Voitsekhovich, O.; Aliev, K.A.; Bilotkach, U.V.

    1997-01-01

    Since May 1986 in Kiev in the Institute of Mathematical Machines and System Problems, Cybernetics Center of the National Academy of Sciences of Ukraine has been started the development of the computerised system for processing of Dniper basin radiological monitoring data and modelling of radionuclide dispersion in rivers and reservoirs. For this work it was established the Interdisciplinary Working Group that joints the specialists from the State Committee of Water Resources, State Committee of Hydrometeorology, National Academy of Sciences and other Ukrainian institutions. The objectives of the computerized system development were formulated by the State Emergency Commission and later by the Ukrainian Minchernobyl as follows: reliable evaluation of the surface water contamination at Pripyat River and Dnieper River on the basis of monitoring data from the different institutions; seasonal and long-term prediction of the surface water radioactive contamination; decision support for the aquatic post-accidental countermeasures, directed to diminish the radionuclides fluxes from the Chernobyl area through the Pripyat River and Dnieper Reservoirs; decision support for the countermeasures directed on changes in the water assumption

  14. Application of Integrated Reservoir Management and Reservoir Characterization to Optimize Infill Drilling

    Energy Technology Data Exchange (ETDEWEB)

    P. K. Pande

    1998-10-29

    Initial drilling of wells on a uniform spacing, without regard to reservoir performance and characterization, must become a process of the past. Such efforts do not optimize reservoir development as they fail to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, and carbonate reservoirs in particular. These reservoirs are typically characterized by: o Large, discontinuous pay intervals o Vertical and lateral changes in reservoir properties o Low reservoir energy o High residual oil saturation o Low recovery efficiency

  15. Performance reliability prediction for thermal aging based on kalman filtering

    International Nuclear Information System (INIS)

    Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

    2015-01-01

    The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

  16. The prediction of swimming performance in competition from behavioral information.

    Science.gov (United States)

    Rushall, B S; Leet, D

    1979-06-01

    The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

  17. Predicting Performance in Higher Education Using Proximal Predictors

    Science.gov (United States)

    Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

  18. All-optical reservoir computing.

    Science.gov (United States)

    Duport, François; Schneider, Bendix; Smerieri, Anteo; Haelterman, Marc; Massar, Serge

    2012-09-24

    Reservoir Computing is a novel computing paradigm that uses a nonlinear recurrent dynamical system to carry out information processing. Recent electronic and optoelectronic Reservoir Computers based on an architecture with a single nonlinear node and a delay loop have shown performance on standardized tasks comparable to state-of-the-art digital implementations. Here we report an all-optical implementation of a Reservoir Computer, made of off-the-shelf components for optical telecommunications. It uses the saturation of a semiconductor optical amplifier as nonlinearity. The present work shows that, within the Reservoir Computing paradigm, all-optical computing with state-of-the-art performance is possible.

  19. Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

    Science.gov (United States)

    Boone, Spencer

    2017-01-01

    This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

  20. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  1. Proactive Supply Chain Performance Management with Predictive Analytics

    Directory of Open Access Journals (Sweden)

    Nenad Stefanovic

    2014-01-01

    Full Text Available Today’s business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators. Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  2. Proactive Supply Chain Performance Management with Predictive Analytics

    Science.gov (United States)

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605

  3. Proactive supply chain performance management with predictive analytics.

    Science.gov (United States)

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  4. Reservoir water level forecasting using group method of data handling

    Science.gov (United States)

    Zaji, Amir Hossein; Bonakdari, Hossein; Gharabaghi, Bahram

    2018-06-01

    Accurately forecasted reservoir water level is among the most vital data for efficient reservoir structure design and management. In this study, the group method of data handling is combined with the minimum description length method to develop a very practical and functional model for predicting reservoir water levels. The models' performance is evaluated using two groups of input combinations based on recent days and recent weeks. Four different input combinations are considered in total. The data collected from Chahnimeh#1 Reservoir in eastern Iran are used for model training and validation. To assess the models' applicability in practical situations, the models are made to predict a non-observed dataset for the nearby Chahnimeh#4 Reservoir. According to the results, input combinations (L, L -1) and (L, L -1, L -12) for recent days with root-mean-squared error (RMSE) of 0.3478 and 0.3767, respectively, outperform input combinations (L, L -7) and (L, L -7, L -14) for recent weeks with RMSE of 0.3866 and 0.4378, respectively, with the dataset from https://www.typingclub.com/st. Accordingly, (L, L -1) is selected as the best input combination for making 7-day ahead predictions of reservoir water levels.

  5. Hybrid ANFIS with ant colony optimization algorithm for prediction of shear wave velocity from a carbonate reservoir in Iran

    Directory of Open Access Journals (Sweden)

    Hadi Fattahi

    2016-12-01

    Full Text Available Shear wave velocity (Vs data are key information for petrophysical, geophysical and geomechanical studies. Although compressional wave velocity (Vp measurements exist in almost all wells, shear wave velocity is not recorded for most of elderly wells due to lack of technologic tools. Furthermore, measurement of shear wave velocity is to some extent costly. This study proposes a novel methodology to remove aforementioned problems by use of hybrid adaptive neuro fuzzy inference system (ANFIS with ant colony optimization algorithm (ACO based on fuzzy c–means clustering (FCM and subtractive clustering (SCM. The ACO is combined with two ANFIS models for determining the optimal value of its user–defined parameters. The optimization implementation by the ACO significantly improves the generalization ability of the ANFIS models. These models are used in this study to formulate conventional well log data into Vs in a quick, cheap, and accurate manner. A total of 3030 data points was used for model construction and 833 data points were employed for assessment of ANFIS models. Finally, a comparison among ANFIS models, and six well–known empirical correlations demonstrated ANFIS models outperformed other methods. This strategy was successfully applied in the Marun reservoir, Iran.

  6. IMPROVED MISCIBLE NITROGEN FLOOD PERFORMANCE UTILIZING ADVANCED RESERVOIR CHARACTERIZATION AND HORIZONTAL LATERALS IN A CLASS I RESERVOIR - EAST BINGER (MARCHAND) UNIT

    International Nuclear Information System (INIS)

    Sinner, Joe

    2004-01-01

    Budget Period 2 of the East Binger Unit (''EBU'') DOE Project has been. Recent activities included additional data gathering and project monitoring, plus initiation of work on an SPE paper on the modeling efforts of the project. Early production performance suggests horizontal wells do not provide sufficient additional production over vertical wells to justify their incremental cost. It will take more time to evaluate the impact of the horizontal wells on sweep and ultimate recovery, but it is unlikely that an improvement in recovery will be sufficient to make the overall economic value of horizontal wells greater than the economic value of vertical wells. Monitoring of overall performance of the pilot area continues. Overall response to the various projects continues to be very favorable. Injection into the pilot area has nearly doubled, while gas production and nitrogen content of produced gas have both decreased. Nitrogen recycle within the pilot area has dropped from 60% to 20%. Efforts to further disseminate knowledge gained through this project, by means of technical paper presentations to industry groups, are underway. Project monitoring and technology transfer will be focus areas of Budget Period 3

  7. Enhancing pavement performance prediction models for the Illinois Tollway System

    Directory of Open Access Journals (Sweden)

    Laxmikanth Premkumar

    2016-01-01

    Full Text Available Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway with over 2000 lane miles of pavement utilizes the condition rating survey (CRS methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT are used by the Tollway to predict the future condition of its network. The model projects future CRS ratings based on pavement type, thickness, traffic, pavement age and current CRS rating. However, with time and inclusion of newer pavement types there was a need to calibrate the existing pavement performance models, as well as, develop models for newer pavement types.This study presents the results of calibrating the existing models, and developing new models for the various pavement types in the Illinois Tollway network. The predicted future condition of the pavements is used in estimating its remaining service life to failure, which is of immediate use in recommending future maintenance and rehabilitation requirements for the network. Keywords: Pavement performance models, Remaining life, Pavement management

  8. Predicting university performance in psychology: the role of previous performance and discipline-specific knowledge

    OpenAIRE

    Betts, LR; Elder, TJ; Hartley, J; Blurton, A

    2008-01-01

    Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry qualifications predicted: (1) their performance in years 1-3 of their Psychology degree, and (2) their overall degree performance. Students' overall...

  9. The Search Performance Evaluation and Prediction in Exploratory Search

    OpenAIRE

    LIU, FEI

    2016-01-01

    The exploratory search for complex search tasks requires an effective search behavior model to evaluate and predict user search performance. Few studies have investigated the relationship between user search behavior and search performance in exploratory search. This research adopts a mixed approach combining search system development, user search experiment, search query log analysis, and multivariate regression analysis to resolve the knowledge gap. Through this study, it is shown that expl...

  10. Predictive Bias and Sensitivity in NRC Fuel Performance Codes

    Energy Technology Data Exchange (ETDEWEB)

    Geelhood, Kenneth J.; Luscher, Walter G.; Senor, David J.; Cunningham, Mitchel E.; Lanning, Donald D.; Adkins, Harold E.

    2009-10-01

    The latest versions of the fuel performance codes, FRAPCON-3 and FRAPTRAN were examined to determine if the codes are intrinsically conservative. Each individual model and type of code prediction was examined and compared to the data that was used to develop the model. In addition, a brief literature search was performed to determine if more recent data have become available since the original model development for model comparison.

  11. STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

    OpenAIRE

    S.A. Oloruntoba1 ,J.L.Akinode2

    2017-01-01

    This paper investigates the relationship between students' preadmission academic profile and final academic performance. Data Sample of students in one of the Federal Polytechnic in south West part of Nigeria was used. The preadmission academic profile used for this study is the 'O' level grades(terminal high school results).The academic performance is defined using student's Grade Point Average(GPA). This research focused on using data mining technique to develop a model for predicting stude...

  12. Children's biological responsivity to acute stress predicts concurrent cognitive performance.

    Science.gov (United States)

    Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

    2018-04-10

    Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

  13. Predicting long-term performance of engineered geologic carbon dioxide storage systems to inform decisions amidst uncertainty

    Science.gov (United States)

    Pawar, R.

    2016-12-01

    Risk assessment and risk management of engineered geologic CO2 storage systems is an area of active investigation. The potential geologic CO2 storage systems currently under consideration are inherently heterogeneous and have limited to no characterization data. Effective risk management decisions to ensure safe, long-term CO2 storage requires assessing and quantifying risks while taking into account the uncertainties in a storage site's characteristics. The key decisions are typically related to definition of area of review, effective monitoring strategy and monitoring duration, potential of leakage and associated impacts, etc. A quantitative methodology for predicting a sequestration site's long-term performance is critical for making key decisions necessary for successful deployment of commercial scale geologic storage projects where projects will require quantitative assessments of potential long-term liabilities. An integrated assessment modeling (IAM) paradigm which treats a geologic CO2 storage site as a system made up of various linked subsystems can be used to predict long-term performance. The subsystems include storage reservoir, seals, potential leakage pathways (such as wellbores, natural fractures/faults) and receptors (such as shallow groundwater aquifers). CO2 movement within each of the subsystems and resulting interactions are captured through reduced order models (ROMs). The ROMs capture the complex physical/chemical interactions resulting due to CO2 movement and interactions but are computationally extremely efficient. The computational efficiency allows for performing Monte Carlo simulations necessary for quantitative probabilistic risk assessment. We have used the IAM to predict long-term performance of geologic CO2 sequestration systems and to answer questions related to probability of leakage of CO2 through wellbores, impact of CO2/brine leakage into shallow aquifer, etc. Answers to such questions are critical in making key risk management

  14. Analysis of Factors that Predict Clinical Performance in Medical School

    Science.gov (United States)

    White, Casey B.; Dey, Eric L.; Fantone, Joseph C.

    2009-01-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT…

  15. Predicting Performance in Higher Education Using Proximal Predictors

    NARCIS (Netherlands)

    Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach,

  16. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

  17. Image processing system performance prediction and product quality evaluation

    Science.gov (United States)

    Stein, E. K.; Hammill, H. B. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

  18. Predicting High-Power Performance in Professional Cyclists.

    Science.gov (United States)

    Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

    2017-03-01

    To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

  19. Injectivity decline prediction for Campos Basin reservoirs; Previsao da perda de injetividade para reservatorios da Bacia de Campos

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Adriano dos [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil); Bedrikovetsky, Pavel [Universidade Estadual do Norte Fluminense (UENF), Campos dos Goytacazes, RJ (Brazil); Furtado, Claudio J.A. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)

    2008-07-01

    A simulator for prediction of injectivity decline in perforated water injection wells is presented. The model parameters (filtration and formation damage coefficients) were determined from history data fitting, allowing injectivity decline prediction for various perforated water injectors. The injectivity model, considering both internal and external filtration, fitted the history data very well and allowed a comprehensive analysis of injectivity decline. The simulations revealed that, after the perforations filling, the injectivity decline rate becomes much more intensive. Therefore, the time necessary for perforations filling is an important variable on work over planning. (author)

  20. Entity versus incremental theories predict older adults' memory performance.

    Science.gov (United States)

    Plaks, Jason E; Chasteen, Alison L

    2013-12-01

    The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  1. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  2. Reservoir sedimentation; a literature survey

    NARCIS (Netherlands)

    Sloff, C.J.

    1991-01-01

    A survey of literature is made on reservoir sedimentation, one of the most threatening processes for world-wide reservoir performance. The sedimentation processes, their impacts, and their controlling factors are assessed from a hydraulic engineering point of view with special emphasis on

  3. Calibration between Undergraduate Students' Prediction of and Actual Performance: The Role of Gender and Performance Attributions

    Science.gov (United States)

    Gutierrez, Antonio P.; Price, Addison F.

    2017-01-01

    This study investigated changes in male and female students' prediction and postdiction calibration accuracy and bias scores, and the predictive effects of explanatory styles on these variables beyond gender. Seventy undergraduate students rated their confidence in performance before and after a 40-item exam. There was an improvement in students'…

  4. Predictive Measures of Locomotor Performance on an Unstable Walking Surface

    Science.gov (United States)

    Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.; hide

    2016-01-01

    Locomotion requires integration of visual, vestibular, and somatosensory information to produce the appropriate motor output to control movement. The degree to which these sensory inputs are weighted and reorganized in discordant sensory environments varies by individual and may be predictive of the ability to adapt to novel environments. The goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to inform the design of training countermeasures designed to enhance the ability of astronauts to adapt to gravitational transitions improving balance and locomotor performance after a Mars landing and enhancing egress capability after a landing on Earth.

  5. Predicting Performance on MOOC Assessments using Multi-Regression Models

    OpenAIRE

    Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya

    2016-01-01

    The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent may achieve on a given grade-related assessment based on information, considered as prior performance or prior ac- tivity in the course. We develop a personalized linear mul- tiple regression (PLMR) model to predict the grade for a student, prior to attempt...

  6. Simplified Predictive Models for CO2 Sequestration Performance Assessment

    Science.gov (United States)

    Mishra, Srikanta; RaviGanesh, Priya; Schuetter, Jared; Mooney, Douglas; He, Jincong; Durlofsky, Louis

    2014-05-01

    We present results from an ongoing research project that seeks to develop and validate a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formation. The overall research goal is to provide tools for predicting: (a) injection well and formation pressure buildup, and (b) lateral and vertical CO2 plume migration. Simplified modeling approaches that are being developed in this research fall under three categories: (1) Simplified physics-based modeling (SPM), where only the most relevant physical processes are modeled, (2) Statistical-learning based modeling (SLM), where the simulator is replaced with a "response surface", and (3) Reduced-order method based modeling (RMM), where mathematical approximations reduce the computational burden. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. In the first category (SPM), we use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. In the second category (SLM), we develop statistical "proxy models" using the simulation domain described previously with two different approaches: (a) classical Box-Behnken experimental design with a quadratic response surface fit, and (b) maximin Latin Hypercube sampling (LHS) based design with a Kriging metamodel fit using a quadratic trend and Gaussian correlation structure. For roughly the same number of

  7. Real-time Tsunami Inundation Prediction Using High Performance Computers

    Science.gov (United States)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  8. Coupled Heuristic Prediction of Long Lead-Time Accumulated Total Inflow of a Reservoir during Typhoons Using Deterministic Recurrent and Fuzzy Inference-Based Neural Network

    Directory of Open Access Journals (Sweden)

    Chien-Lin Huang

    2015-11-01

    Full Text Available This study applies Real-Time Recurrent Learning Neural Network (RTRLNN and Adaptive Network-based Fuzzy Inference System (ANFIS with novel heuristic techniques to develop an advanced prediction model of accumulated total inflow of a reservoir in order to solve the difficulties of future long lead-time highly varied uncertainty during typhoon attacks while using a real-time forecast. For promoting the temporal-spatial forecasted precision, the following original specialized heuristic inputs were coupled: observed-predicted inflow increase/decrease (OPIID rate, total precipitation, and duration from current time to the time of maximum precipitation and direct runoff ending (DRE. This study also investigated the temporal-spatial forecasted error feature to assess the feasibility of the developed models, and analyzed the output sensitivity of both single and combined heuristic inputs to determine whether the heuristic model is susceptible to the impact of future forecasted uncertainty/errors. Validation results showed that the long lead-time–predicted accuracy and stability of the RTRLNN-based accumulated total inflow model are better than that of the ANFIS-based model because of the real-time recurrent deterministic routing mechanism of RTRLNN. Simulations show that the RTRLNN-based model with coupled heuristic inputs (RTRLNN-CHI, average error percentage (AEP/average forecast lead-time (AFLT: 6.3%/49 h can achieve better prediction than the model with non-heuristic inputs (AEP of RTRLNN-NHI and ANFIS-NHI: 15.2%/31.8% because of the full consideration of real-time hydrological initial/boundary conditions. Besides, the RTRLNN-CHI model can promote the forecasted lead-time above 49 h with less than 10% of AEP which can overcome the previous forecasted limits of 6-h AFLT with above 20%–40% of AEP.

  9. A comparison of SAR ATR performance with information theoretic predictions

    Science.gov (United States)

    Blacknell, David

    2003-09-01

    Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

  10. Prediction of Tennis Performance in Junior Elite Tennis Players

    Directory of Open Access Journals (Sweden)

    Tamara Kramer, Barbara C.H. Huijgen, Marije T. Elferink-Gemser, Chris Visscher

    2017-03-01

    Full Text Available Predicting current and future tennis performance can lead to improving the development of junior tennis players. The aim of this study is to investigate whether age, maturation, or physical fitness in junior elite tennis players in U13 can explain current and future tennis performance. The value of current tennis performance for future tennis performance is also investigated. A total of 86 junior elite tennis players (boys, n = 44; girls, n = 42 U13 (aged: 12.5 ± 0.3 years, and followed to U16, took part in this study. All players were top-30 ranked on the Dutch national ranking list at U13, and top-50 at U16. Age, maturation, and physical fitness, were measured at U13. A principal component analysis was used to extract four physical components from eight tests (medicine ball throwing overhead and reverse, ball throwing, SJ, CMJas, Sprint 5 and 10 meter, and the spider test. The possible relationship of age, maturation, and the physical components; “upper body power”, “lower body power”, “speed”, and “agility” with tennis performance at U13 and U16 was analyzed. Tennis performance was measured by using the ranking position on the Dutch national ranking list at U13 and U16. Regression analyses were conducted based on correlations between variables and tennis performance for boys and girls, separately. In boys U13, positive correlations were found between upper body power and tennis performance (R2 is 25%. In girls, positive correlations between maturation and lower body power with tennis performance were found at U13. Early maturing players were associated with a better tennis performance (R2 is 15%. In girls U16, only maturation correlated with tennis performance (R2 is 13%; later-maturing girls at U13 had better tennis performances at U16. Measuring junior elite tennis players at U13 is important for monitoring their development. These measurements did not predict future tennis performance of junior elite tennis players three

  11. Parallel reservoir simulator computations

    International Nuclear Information System (INIS)

    Hemanth-Kumar, K.; Young, L.C.

    1995-01-01

    The adaptation of a reservoir simulator for parallel computations is described. The simulator was originally designed for vector processors. It performs approximately 99% of its calculations in vector/parallel mode and relative to scalar calculations it achieves speedups of 65 and 81 for black oil and EOS simulations, respectively on the CRAY C-90

  12. Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model

    Directory of Open Access Journals (Sweden)

    Yu-Ri Kim

    2016-03-01

    Full Text Available Recently, the Korean government has enforced disclosure of building energy performance, so that such information can help owners and prospective buyers to make suitable investment plans. Such a building energy performance policy of the government makes it mandatory for the building owners to obtain engineering audits and thereby evaluate the energy performance levels of their buildings. However, to calculate energy performance levels (i.e., asset rating methodology, a qualified expert needs to have access to at least the full project documentation and/or conduct an on-site inspection of the buildings. Energy performance certification costs a lot of time and money. Moreover, the database of certified buildings is still actually quite small. A need, therefore, is increasing for a simplified and user-friendly energy performance prediction tool for non-specialists. Also, a database which allows building owners and users to compare best practices is required. In this regard, the current study developed a simplified performance prediction model through experimental design, energy simulations and ANOVA (analysis of variance. Furthermore, using the new prediction model, a related mobile application was also developed.

  13. When predictions take control: The effect of task predictions on task switching performance

    Directory of Open Access Journals (Sweden)

    Wout eDuthoo

    2012-08-01

    Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

  14. MAPPING OF RESERVOIR PROPERTIES AND FACIES THROUGH INTEGRATION OF STATIC AND DYNAMIC DATA

    Energy Technology Data Exchange (ETDEWEB)

    Albert C. Reynolds; Dean S. Oliver; Fengjun Zhang; Yannong Dong; Jan Arild Skjervheim; Ning Liu

    2003-01-01

    Knowledge of the distribution of permeability and porosity in a reservoir is necessary for the prediction of future oil production, estimation of the location of bypassed oil, and optimization of reservoir management. But while the volume of data that can potentially provide information on reservoir architecture and fluid distributions has increased enormously in the past decade, it is not yet possible to make use of all the available data in an integrated fashion. While it is relatively easy to generate plausible reservoir models that honor static data such as core, log, and seismic data, it is far more difficult to generate plausible reservoir models that honor dynamic data such as transient pressures, saturations, and flow rates. As a result, the uncertainty in reservoir properties is higher than it could be and reservoir management can not be optimized. The goal of this project is to develop computationally efficient automatic history matching techniques for generating geologically plausible reservoir models which honor both static and dynamic data. Solution of this problem is necessary for the quantification of uncertainty in future reservoir performance predictions and for the optimization of reservoir management. Facies (defined here as regions of relatively uniform petrophysical properties) are common features of all reservoirs. Because the flow properties of the various facies can vary greatly, knowledge of the location of facies boundaries is of utmost importance for the prediction of reservoir performance and for the optimization of reservoir management. When the boundaries between facies are fairly well known, but flow properties are poorly known, the average properties for all facies can be determined using traditional techniques. Traditional history matching honors dynamic data by adjusting petrophysical properties in large areas, but in the process of adjusting the reservoir model ignores the static data and often results in implausible reservoir

  15. Genomic Prediction of Testcross Performance in Canola (Brassica napus)

    Science.gov (United States)

    Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

    2016-01-01

    Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable

  16. Modeling and prediction of flotation performance using support vector regression

    Directory of Open Access Journals (Sweden)

    Despotović Vladimir

    2017-01-01

    Full Text Available Continuous efforts have been made in recent year to improve the process of paper recycling, as it is of critical importance for saving the wood, water and energy resources. Flotation deinking is considered to be one of the key methods for separation of ink particles from the cellulose fibres. Attempts to model the flotation deinking process have often resulted in complex models that are difficult to implement and use. In this paper a model for prediction of flotation performance based on Support Vector Regression (SVR, is presented. Representative data samples were created in laboratory, under a variety of practical control variables for the flotation deinking process, including different reagents, pH values and flotation residence time. Predictive model was created that was trained on these data samples, and the flotation performance was assessed showing that Support Vector Regression is a promising method even when dataset used for training the model is limited.

  17. Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes

    Science.gov (United States)

    2015-05-01

    Metabolic energy consumption as a function of speed and body size in birds and mammals. J Exp Biol. 97, 1-21. Weyand, P., Smith, B., Puyau, M. and...height, weight (including load), speed, and grade algorithms proposed will allow walking metabolic rates to be predicted to within 6.0 and 12.0% in...gait, metabolism , performance, load carriage 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME

  18. Decline Curve Based Models for Predicting Natural Gas Well Performance

    OpenAIRE

    Kamari, Arash; Mohammadi, Amir H.; Lee, Moonyong; Mahmood, Tariq; Bahadori, Alireza

    2016-01-01

    The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN) modelling strategy, least square support vector machine (LSSVM) approach, adaptive neuro-fuzzy ...

  19. Sexual victimization history predicts academic performance in college women.

    Science.gov (United States)

    Baker, Majel R; Frazier, Patricia A; Greer, Christiaan; Paulsen, Jacob A; Howard, Kelli; Meredith, Liza N; Anders, Samantha L; Shallcross, Sandra L

    2016-11-01

    College women frequently report having experienced sexual victimization (SV) in their lifetime, including child sexual abuse and adolescent/adult sexual assault. Although the harmful mental health sequelae of SV have been extensively studied, recent research suggests that SV is also a risk factor for poorer college academic performance. The current studies examined whether exposure to SV uniquely predicted poorer college academic performance, even beyond contributions from three well-established predictors of academic performance: high school rank, composite standardized test scores (i.e., American College Testing [ACT]), and conscientiousness. Study 1 analyzed longitudinal data from a sample of female college students (N = 192) who were assessed at the beginning and end of one semester. SV predicted poorer cumulative end-of-semester grade point average (GPA) while controlling for well-established predictors of academic performance. Study 2 replicated these findings in a second longitudinal study of female college students (N = 390) and extended the analyses to include follow-up data on the freshmen and sophomore students (n = 206) 4 years later. SV predicted students' GPA in their final term at the university above the contributions of well-established academic predictors, and it was the only factor related to leaving college. These findings highlight the importance of expanding the scope of outcomes of SV to include academic performance, and they underscore the need to assess SV and other adverse experiences on college campuses to target students who may be at risk of poor performance or leaving college. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. Applicability of WRF-Lake System in Studying Reservoir-Induced Impacts on Local Climate: Case Study of Two Reservoirs with Contrasting Characteristics

    Science.gov (United States)

    Wang, F.; Zhu, D.; Ni, G.; Sun, T.

    2017-12-01

    Large reservoirs play a key role in regional hydrological cycles as well as in modulating the local climate. The emerging large reservoirs in concomitant with rapid hydropower exploitation in southwestern China warrant better understanding of their impacts on local and regional climates. One of the crucial pathways through which reservoirs impact the climate is lake-atmospheric interaction. Although such interactions have been widely studied with numeric weather prediction (NWP) models, an outstanding limitation across various NWPs resides on the poor thermodynamic representation of lakes. The recent version of Weather Research and Forecasting (WRF) system has been equipped with a one-dimensional lake model to better represent the thermodynamics of large water body and has been shown to enhance the its predication skill in the lake-atmospheric interaction. In this study, we further explore the applicability of the WRF-Lake system in two reservoirs with contrasting characteristics: Miyun Reservoir with an average depth of 30 meters in North China Plain, and Nuozhadu Reservoir with an average depth of 200 meters in the Tibetan Plateau Region. Driven by the high spatiotemporal resolution meteorological forcing data, the WRF-Lake system is used to simulate the water temperature and surface energy budgets of the two reservoirs after the evaluation against temperature observations. The simulated results show the WRF-Lake model can well predict the vertical profile of water temperature in Miyun Reservoir, but underestimates deep water temperature and overestimates surface temperature in the deeper Nuozhadu Reservoir. In addition, sensitivity analysis indicates the poor performance of the WRF-Lake system in Nuozhadu Reservoir could be attributed to the weak vertical mixing in the model, which can be improved by tuning the eddy diffusion coefficient ke . Keywords: reservoir-induced climatic impact; lake-atmospheric interaction; WRF-Lake system; hydropower exploitation

  1. Predicting work Performance through selection interview ratings and Psychological assessment

    Directory of Open Access Journals (Sweden)

    Liziwe Nzama

    2008-11-01

    Full Text Available The aim of the study was to establish whether selection interviews used in conjunction with psychological assessments of personality traits and cognitive functioning contribute to predicting work performance. The sample consisted of 102 managers who were appointed recently in a retail organisation. The independent variables were selection interview ratings obtained on the basis of structured competency-based interview schedules by interviewing panels, fve broad dimensions of personality defned by the Five Factor Model as measured by the 15 Factor Questionnaire (15FQ+, and cognitive processing variables (current level of work, potential level of work, and 12 processing competencies measured by the Cognitive Process Profle (CPP. Work performance was measured through annual performance ratings that focused on measurable outputs of performance objectives. Only two predictor variables correlated statistically signifcantly with the criterion variable, namely interview ratings (r = 0.31 and CPP Verbal Abstraction (r = 0.34. Following multiple regression, only these variables contributed signifcantly to predicting work performance, but only 17.8% of the variance of the criterion was accounted for.

  2. Production of Natural Gas and Fluid Flow in Tight Sand Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Maria Cecilia Bravo

    2006-06-30

    This document reports progress of this research effort in identifying relationships and defining dependencies between macroscopic reservoir parameters strongly affected by microscopic flow dynamics and production well performance in tight gas sand reservoirs. These dependencies are investigated by identifying the main transport mechanisms at the pore scale that should affect fluids flow at the reservoir scale. A critical review of commercial reservoir simulators, used to predict tight sand gas reservoir, revealed that many are poor when used to model fluid flow through tight reservoirs. Conventional simulators ignore altogether or model incorrectly certain phenomena such as, Knudsen diffusion, electro-kinetic effects, ordinary diffusion mechanisms and water vaporization. We studied the effect of Knudsen's number in Klinkenberg's equation and evaluated the effect of different flow regimes on Klinkenberg's parameter b. We developed a model capable of explaining the pressure dependence of this parameter that has been experimentally observed, but not explained in the conventional formalisms. We demonstrated the relevance of this, so far ignored effect, in tight sands reservoir modeling. A 2-D numerical simulator based on equations that capture the above mentioned phenomena was developed. Dynamic implications of new equations are comprehensively discussed in our work and their relative contribution to the flow rate is evaluated. We performed several simulation sensitivity studies that evidenced that, in general terms, our formalism should be implemented in order to get more reliable tight sands gas reservoirs' predictions.

  3. Fiscal 1999 research and verification of geothermal energy exploring technologies and the like. Development of reservoir mass and heat flow characterization (Development of reservoir change prediction technology - Summary); 1999 nendo chinetsu tansa gijutsu nado kensho chosa hokokusho (yoyaku). Choryuso hendo tansaho kaihatsu (choryuso hendo yosoku gijutsu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-03-01

    Efforts are exerted to develop technologies for accurately predicting reservoir expansion or other changes through a comprehensive analysis of the fracture hydrology method, gravity monitoring method, electrical and magnetic monitoring method, seismic monitoring method, and their associated technologies. The endeavors cover the development of a post processor system which involves gravity, self-potential, geochemistry, resistivity, etc., and is related to a reservoir simulator, and the development of a reservoir modelling technology. For the development of a post processor system, efforts continue (1) to develop a processor to deal with gravity, self-potential, resistivity, and geochemistry, (2) to carry out basic studies of changes in seismic propagation characteristics, (3) to develop databases, and (4) to develop a simulator interface. Under item (1), development involving gravity, self-potential, and geochemistry is complete, and now manuals are being prepared. A prototype design is complete for resistivity. For the development of a reservoir modelling technology, modelling is under way for the Onikobe and Sumikawa districts. Existing data are taken care of, and productivity predicting simulation is carried out. (NEDO)

  4. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    Directory of Open Access Journals (Sweden)

    Heung-Il Suk

    Full Text Available Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

  5. Cognitive load predicts point-of-care ultrasound simulator performance.

    Science.gov (United States)

    Aldekhyl, Sara; Cavalcanti, Rodrigo B; Naismith, Laura M

    2018-02-01

    The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice.

  6. The effects of intercooling and regeneration on the thermo-ecological performance analysis of an irreversible-closed Brayton heat engine with variable-temperature thermal reservoirs

    International Nuclear Information System (INIS)

    Sogut, Oguz Salim; Ust, Yasin; Sahin, Bahri

    2006-01-01

    A thermo-ecological performance analysis of an irreversible intercooled and regenerated closed Brayton heat engine exchanging heat with variable-temperature thermal reservoirs is presented. The effects of intercooling and regeneration are given special emphasis and investigated in detail. A comparative performance analysis considering the objective functions of an ecological coefficient of performance, an ecological function proposed by Angulo-Brown and power output is also carried out. The results indicate that the optimal total isentropic temperature ratio and intercooling isentropic temperature ratio at the maximum ecological coefficient of performance conditions (ECOP max ) are always less than those of at the maximum ecological function ( E-dot max ) and the maximum power output conditions ( W-dot max ) leading to a design that requires less investment cost. It is also concluded that a design at ECOP max conditions has the advantage of higher thermal efficiency and a lesser entropy generation rate, but at the cost of a slight power loss

  7. Decline curve based models for predicting natural gas well performance

    Directory of Open Access Journals (Sweden)

    Arash Kamari

    2017-06-01

    Full Text Available The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN modelling strategy, least square support vector machine (LSSVM approach, adaptive neuro-fuzzy inference system (ANFIS, and decision tree (DT method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps' decline curve exponent and ratio of initial gas flow rate over total gas flow rate. It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data. Furthermore, the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production, and initial decline rate multiplied by time.

  8. Performance and wake predictions of HAWTs in wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)

    1997-12-31

    The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

  9. Cesium reservoir and interconnective components

    International Nuclear Information System (INIS)

    1994-03-01

    The program objective is to demonstrate the technology readiness of a TFE (thermionic fuel element) suitable for use as the basic element in a thermionic reactor with electric power output in the 0.5 to 5.0 MW range. A thermionic converter must be supplied with cesium vapor for two reasons. Cesium atoms adsorbed on the surface of the emitter cause a reduction of the emitter work function to permit high current densities without excessive heating of the emitter. The second purpose of the cesium vapor is to provide space-charge neutralization in the emitter-collector gap so that the high current densities may flow across the gap unattenuated. The function of the cesium reservoir is to provide a source of cesium atoms, and to provide a reserve in the event that cesium is lost from the plasma by any mechanism. This can be done with a liquid cesium metal reservoir in which case it is heated to the desired temperature with auxiliary heaters. In a TFE, however, it is desirable to have the reservoir passively heated by the nuclear fuel. In this case, the reservoir must operate at a temperature intermediate between the emitter and the collector, ruling out the use of liquid reservoirs. Integral reservoirs contained within the TFE will produce cesium vapor pressures in the desired range at typical electrode temperatures. The reservoir material that appears to be the best able to meet requirements is graphite. Cesium intercalates easily into graphite, and the cesium pressure is insensitive to loading for a given intercalation stage. The goals of the cesium reservoir test program were to verify the performance of Cs-graphite reservoirs in the temperature-pressure range of interest to TFE operation, and to test the operation of these reservoirs after exposure to a fast neutron fluence corresponding to seven year mission lifetime. In addition, other materials were evaluated for possible use in the integral reservoir

  10. Predicting introductory programming performance: A multi-institutional multivariate study

    Science.gov (United States)

    Bergin, Susan; Reilly, Ronan

    2006-12-01

    A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

  11. Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)

    2006-11-01

    The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensor packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging

  12. Numerical simulation of a twin screw expander for performance prediction

    Science.gov (United States)

    Papes, Iva; Degroote, Joris; Vierendeels, Jan

    2015-08-01

    With the increasing use of twin screw expanders in waste heat recovery applications, the performance prediction of these machines plays an important role. This paper presents a mathematical model for calculating the performance of a twin screw expander. From the mass and energy conservation laws, differential equations are derived which are then solved together with the appropriate Equation of State in the instantaneous control volumes. Different flow processes that occur inside the screw expander such as filling (accompanied by a substantial pressure loss) and leakage flows through the clearances are accounted for in the model. The mathematical model employs all geometrical parameters such as chamber volume, suction and leakage areas. With R245fa as working fluid, the Aungier Redlich-Kwong Equation of State has been used in order to include real gas effects. To calculate the mass flow rates through the leakage paths formed inside the screw expander, flow coefficients are considered as constant and they are derived from 3D Computational Fluid Dynamic calculations at given working conditions and applied to all other working conditions. The outcome of the mathematical model is the P-V indicator diagram which is compared to CFD results of the same twin screw expander. Since CFD calculations require significant computational time, developed mathematical model can be used for the faster performance prediction.

  13. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    Directory of Open Access Journals (Sweden)

    Amber Watts PhD

    2015-08-01

    Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

  14. Prediction of performance and evaluation of flexible pavement rehabilitation strategies

    Directory of Open Access Journals (Sweden)

    Kang-Won Wayne Lee

    2017-04-01

    Full Text Available Five test sections with different additives and strategies were established to rehabilitate a State-maintained highway more effectively in Rhode Island (RI: control, calcium chloride, asphalt emulsion, Portland cement and geogrid. Resilient moduli of subgrade soils and subbase materials before and after full depth rehabilitation were employed as input parameters to predict the performance of pavement structures using AASHTOWare Pavement ME Design (Pavement ME software in terms of rutting, cracking and roughness. It was attempted to use Level 1 input (which includes traffic full spectrum data, climate data and structural layer properties for Pavement ME. Traffic data was obtained from a Weigh-in-Motion (WIM instrument and Providence station was used for collecting climatic data. Volumetric properties, dynamic modulus and creep compliance were used as input parameters for 19 mm (0.75 in. warm mix asphalt (WMA base and 12.5 mm (0.5 in. WMA surface layer. The results indicated that all test sections observed AC top-down (longitudinal cracking except Portland cement section which passed for all criteria. The order in terms of performance (best to worst for all test sections by Pavement ME was Portland cement, calcium chloride, control, geogrid, and asphalt emulsion. It was also observed that all test sections passed for both bottom up and top down fatigue cracking by increasing thickness of either of the two top asphalt layers. Test sections with five different base/subbase materials were evaluated in last two years through visual condition survey and measurements of deflection and roughness to confirm the prediction, but there was no serious distress and roughness. Thus these experiments allowed selecting the best rehabilitation/reconstruction techniques for the particular and/or similar highway, and a framework was formulated to select an optimal technique and/or strategy for future rehabilitation/reconstruction projects. Finally, guidelines for

  15. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  16. Bayesian calibration of power plant models for accurate performance prediction

    International Nuclear Information System (INIS)

    Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der

    2014-01-01

    Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

  17. Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information

    Science.gov (United States)

    Yang, Tiantian; Asanjan, Ata Akbari; Welles, Edwin; Gao, Xiaogang; Sorooshian, Soroosh; Liu, Xiaomang

    2017-04-01

    Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for many purposes. Efficient reservoir operation requires policy makers and operators to understand how reservoir inflows are changing under different hydrological and climatic conditions to enable forecast-informed operations. Over the last decade, the uses of Artificial Intelligence and Data Mining [AI & DM] techniques in assisting reservoir streamflow subseasonal to seasonal forecasts have been increasing. In this study, Random Forest [RF), Artificial Neural Network (ANN), and Support Vector Regression (SVR) are employed and compared with respect to their capabilities for predicting 1 month-ahead reservoir inflows for two headwater reservoirs in USA and China. Both current and lagged hydrological information and 17 known climate phenomenon indices, i.e., PDO and ENSO, etc., are selected as predictors for simulating reservoir inflows. Results show (1) three methods are capable of providing monthly reservoir inflows with satisfactory statistics; (2) the results obtained by Random Forest have the best statistical performances compared with the other two methods; (3) another advantage of Random Forest algorithm is its capability of interpreting raw model inputs; (4) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow; and (5) different climate conditions are autocorrelated with up to several months, and the climatic information and their lags are cross correlated with local hydrological conditions in our case studies.

  18. Variability, Predictability, and Race Factors Affecting Performance in Elite Biathlon.

    Science.gov (United States)

    Skattebo, Øyvind; Losnegard, Thomas

    2018-03-01

    To investigate variability, predictability, and smallest worthwhile performance enhancement in elite biathlon sprint events. In addition, the effects of race factors on performance were assessed. Data from 2005 to 2015 including >10,000 and >1000 observations for each sex for all athletes and annual top-10 athletes, respectively, were included. Generalized linear mixed models were constructed based on total race time, skiing time, shooting time, and proportions of targets hit. Within-athlete race-to-race variability was expressed as coefficient of variation of performance times and standard deviation (SD) in proportion units (%) of targets hit. The models were adjusted for random and fixed effects of subject identity, season, event identity, and race factors. The within-athlete variability was independent of sex and performance standard of athletes: 2.5-3.2% for total race time, 1.5-1.8% for skiing time, and 11-15% for shooting times. The SD of the proportion of hits was ∼10% in both shootings combined (meaning ±1 hit in 10 shots). The predictability in total race time was very high to extremely high for all athletes (ICC .78-.84) but trivial for top-10 athletes (ICC .05). Race times during World Championships and Olympics were ∼2-3% faster than in World Cups. Moreover, race time increased by ∼2% per 1000 m of altitude, by ∼5% per 1% of gradient, by 1-2% per 1 m/s of wind speed, and by ∼2-4% on soft vs hard tracks. Researchers and practitioners should focus on strategies that improve biathletes' performance by at least 0.8-0.9%, corresponding to the smallest worthwhile enhancement (0.3 × within-athlete variability).

  19. Predictive neuromechanical simulations indicate why walking performance declines with ageing.

    Science.gov (United States)

    Song, Seungmoon; Geyer, Hartmut

    2018-04-01

    Although the natural decline in walking performance with ageing affects the quality of life of a growing elderly population, its physiological origins remain unknown. By using predictive neuromechanical simulations of human walking with age-related neuro-musculo-skeletal changes, we find evidence that the loss of muscle strength and muscle contraction speed dominantly contribute to the reduced walking economy and speed. The findings imply that focusing on recovering these muscular changes may be the only effective way to improve performance in elderly walking. More generally, the work is of interest for investigating the physiological causes of altered gait due to age, injury and disorders. Healthy elderly people walk slower and energetically less efficiently than young adults. This decline in walking performance lowers the quality of life for a growing ageing population, and understanding its physiological origin is critical for devising interventions that can delay or revert it. However, the origin of the decline in walking performance remains unknown, as ageing produces a range of physiological changes whose individual effects on gait are difficult to separate in experiments with human subjects. Here we use a predictive neuromechanical model to separately address the effects of common age-related changes to the skeletal, muscular and nervous systems. We find in computer simulations of this model that the combined changes produce gait consistent with elderly walking and that mainly the loss of muscle strength and mass reduces energy efficiency. In addition, we find that the slower preferred walking speed of elderly people emerges in the simulations when adapting to muscle fatigue, again mainly caused by muscle-related changes. The results suggest that a focus on recovering these muscular changes may be the only effective way to improve performance in elderly walking. © 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.

  20. Performance Prediction and Validation: Data, Frameworks, and Considerations

    Energy Technology Data Exchange (ETDEWEB)

    Tinnesand, Heidi

    2017-05-19

    Improving the predictability and reliability of wind power generation and operations will reduce costs and potentially establish a framework to attract new capital into the distributed wind sector, a key cost reduction requirement highlighted in results from the distributed wind future market assessment conducted with dWind. Quantifying and refining the accuracy of project performance estimates will also directly address several of the key challenges identified by industry stakeholders in 2015 as part of the distributed wind resource assessment workshop and be cross-cutting for several other facets of the distributed wind portfolio. This presentation covers the efforts undertaken in 2016 to address these topics.

  1. Numerical analysis of the performance prediction for a thermoelectric generator

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang Nyung [Kyung Hee University, Yongin (Korea, Republic of)

    2015-09-15

    The present study develops a two-dimensional numerical code that can predict the performance of a thermoelectric generator module including a p-leg/n-leg pair and top and bottom electrodes. The present code can simulate the detailed thermoelectric phenomena including the heat flow, electric current, Joule heating, Peltier heating, and Thomson heating, together with the efficiency of the modules whose properties depend on the temperature. The present numerical code can be used for the design optimization of a thermoelectric power generator.

  2. Predicting Students’ Performance using Modified ID3 Algorithm

    OpenAIRE

    Ramanathan L; Saksham Dhanda; Suresh Kumar D

    2013-01-01

    The ability to predict performance of students is very crucial in our present education system. We can use data mining concepts for this purpose. ID3 algorithm is one of the famous algorithms present today to generate decision trees. But this algorithm has a shortcoming that it is inclined to attributes with many values. So , this research aims to overcome this shortcoming of the algorithm by using gain ratio(instead of information gain) as well as by giving weights to each attribute at every...

  3. Performance prediction of a multi-basin solar still

    International Nuclear Information System (INIS)

    Mahdi, N.Al.

    1992-01-01

    A transient analysis for the prediction of the performance of a multi-basin solar still is presented. The energy-balance equations for the glass covers, the water masses and the absorber plate are manipulated to obtain a set of ordinary differential equations which are solved numerically. The analysis is applied to investigate the effect of the number of basins on the daily productivity of the still. Meteorological data corresponding to a June day in Bahrain have been used for the computation. The results indicate that the daily distillate output is increased by increasing the number of basins in the still. (author)

  4. Exergoeconomic performance optimization of an endoreversible intercooled regenerative Brayton combined heat and power plant coupled to variable-temperature heat reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Bo; Chen, Lingen; Sun, Fengrui [College of Naval Architecture and Power, Naval University of Engineering, Wuhan 430033 (China)

    2012-07-01

    An endoreversible intercooled regenerative Brayton combined heat and power (CHP) plant model coupled to variable-temperature heat reservoirs is established. The exergoeconomic performance of the CHP plant is investigated using finite time thermodynamics. The analytical formulae about dimensionless profit rate and exergy efficiency of the CHP plant with the heat resistance losses in the hot-, cold- and consumer-side heat exchangers, the intercooler and the regenerator are deduced. By taking the maximum profit rate as the objective, the heat conductance allocation among the five heat exchangers and the choice of intercooling pressure ratio are optimized by numerical examples, the characteristic of the optimal dimensionless profit rate versus corresponding exergy efficiency is investigated. When the optimization is performed further with respect to the total pressure ratio, a double-maximum profit rate is obtained. The effects of the design parameters on the double-maximum dimensionless profit rate and corresponding exergy efficiency, optimal total pressure ratio and optimal intercooling pressure ratio are analyzed in detail, and it is found that there exist an optimal consumer-side temperature and an optimal thermal capacitance rate matching between the working fluid and the heat reservoir, respectively, corresponding to a thrice-maximum dimensionless profit rate.

  5. Combining water-rock interaction experiments with reaction path and reactive transport modelling to predict reservoir rock evolution in an enhanced geothermal system

    Science.gov (United States)

    Kuesters, Tim; Mueller, Thomas; Renner, Joerg

    2016-04-01

    Reliably predicting the evolution of mechanical and chemical properties of reservoir rocks is crucial for efficient exploitation of enhanced geothermal systems (EGS). For example, dissolution and precipitation of individual rock forming minerals often result in significant volume changes, affecting the hydraulic rock properties and chemical composition of fluid and solid phases. Reactive transport models are typically used to evaluate and predict the effect of the internal feedback of these processes. However, a quantitative evaluation of chemo-mechanical interaction in polycrystalline environments is elusive due to poorly constrained kinetic data of complex mineral reactions. In addition, experimentally derived reaction rates are generally faster than reaction rates determined from natural systems, likely a consequence of the experimental design: a) determining the rate of a single process only, e.g. the dissolution of a mineral, and b) using powdered sample materials and thus providing an unrealistically high reaction surface and at the same time eliminating the restrictions on element transport faced in-situ for fairly dense rocks. In reality, multiple reactions are coupled during the alteration of a polymineralic rocks in the presence of a fluid and the rate determining process of the overall reactions is often difficult to identify. We present results of bulk rock-water interaction experiments quantifying alteration reactions between pure water and a granodiorite sample. The rock sample was chosen for its homogenous texture, small and uniform grain size (˜0.5 mm in diameter), and absence of pre-existing alteration features. The primary minerals are plagioclase (plg - 58 vol.%), quartz (qtz - 21 vol.%), K-feldspar (Kfs - 17 vol.%), biotite (bio - 3 vol.%) and white mica (wm - 1 vol.%). Three sets of batch experiments were conducted at 200 ° C to evaluate the effect of reactive surface area and different fluid path ways using (I) powders of the bulk rock with

  6. Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance.

    Science.gov (United States)

    Vergara, Rodrigo C; Moënne-Loccoz, Cristóbal; Maldonado, Pedro E

    2017-01-01

    Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT), a flanker task (FT) and a counting task (CT). Using multiple linear regression models, we evaluated which variable(s) were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

  7. Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance

    Directory of Open Access Journals (Sweden)

    Rodrigo C. Vergara

    2017-09-01

    Full Text Available Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT, a flanker task (FT and a counting task (CT. Using multiple linear regression models, we evaluated which variable(s were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

  8. Aerodynamic performance prediction of Darrieus-type wind turbines

    Directory of Open Access Journals (Sweden)

    Ion NILĂ

    2010-06-01

    Full Text Available The prediction of Darrieus wind turbine aerodynamic performances provides the necessarydesign and operational data base related to the wind potential. In this sense it provides the type ofturbine suitable to the area where it is to be installed. Two calculation methods are analyzed for arotor with straight blades. The first one is a global method that allows an assessment of the turbinenominal power by a brief calculation. This method leads to an overestimation of performances. Thesecond is the calculation method of the gust factor and momentum which deals with the pale as beingcomposed of different elements that don’t influence each other. This method, developed based on thetheory of the turbine blades, leads to values close to the statistical data obtained experimentally. Thevalues obtained by the calculation method of gust factor - momentum led to the concept of a Darrieusturbine, which will be tested for different wind values in the INCAS subsonic wind tunnel.

  9. Performance prediction of rotary compressor with hydrocarbon refrigerant mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Park, M.W.; Chung, Y.G. [Hanyang University Graduate School, Seoul (Korea); Park, K.W. [LG Industrial System Corporation Limited (Korea); Park, H.Y. [Hanyang University, Seoul (Korea)

    1999-04-01

    This paper presents the modeling approach that can be predicted transient behavior of rotary compressor. Mass and energy conservation laws are applied to the control volume, and real gas state equation is used to obtain thermodynamic properties of refrigerant. The valve equation is solved to analyze discharge process also. Dynamic analysis of vane and roller is carried out to gain friction work. From above modeling, the performance of rotary compressor with radial clearance and friction loss is investigated numerically. The performance of each refrigerant and the possibility of using the hydrocarbon refrigerant mixtures in an existing rotary compressor are estimated by applying R12, R134a, R290/R600a mixture also. (author). 6 refs., 13 figs., 1 tab.

  10. Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

    Science.gov (United States)

    Vecchio, Fabrizio; Miraglia, Francesca; Rossini, Paolo Maria

    2018-05-01

    The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human "Connectome." Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task's performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

  11. Planetary Suit Hip Bearing Model for Predicting Design vs. Performance

    Science.gov (United States)

    Cowley, Matthew S.; Margerum, Sarah; Harvil, Lauren; Rajulu, Sudhakar

    2011-01-01

    , the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.

  12. Fiscal 1997 report of the verification research on geothermal prospecting technology. Theme 5-2. Development of a reservoir change prospecting method (reservoir change prediction technique (modeling support technique)); 1997 nendo chinetsu tansa gijutsu nado kensho chosa. 5-2. Choryuso hendo tansaho kaihatsu (choryuso hendo yosoku gijutsu (modeling shien gijutsu)) hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    To evaluate geothermal reservoirs in the initial stage of development, to keep stable output in service operation, and to develop a technology effective for extraction from peripheral reservoirs, study was made on a reservoir variation prediction technique, in particular, a modeling support technique. This paper describes the result in fiscal 1997. Underground temperature estimation technique using homogenization temperatures of fluid inclusions among core fault system measurement systems was applied to Wasabizawa field. The effect of stretching is important to estimate reservoir temperatures, and use of a minimum homogenization temperature of fluid inclusions in quartz was suitable. Even in the case of no quartz in hydrothermal veins, measured data of quartz (secondary fluid inclusion) in parent rocks adjacent to hydrothermal veins well agreed with measured temperature data. The developmental possibility of a new modeling support technique was confirmed enough through collection of documents and information. Based on the result, measurement equipment suitable for R and D was selected, and a measurement system was established through preliminary experiments. 39 refs., 35 figs., 6 tabs.

  13. The prediction of the hydrodynamic performance of tidal current turbines

    International Nuclear Information System (INIS)

    Xiao, B Y; Zhou, L J; Xiao, Y X; Wang, Z W

    2013-01-01

    Nowadays tidal current energy is considered to be one of the most promising alternative green energy resources and tidal current turbines are used for power generation. Prediction of the open water performance around tidal turbines is important for the reason that it can give some advice on installation and array of tidal current turbines. This paper presents numerical computations of tidal current turbines by using a numerical model which is constructed to simulate an isolated turbine. This paper aims at studying the installation of marine current turbine of which the hydro-environmental impacts influence by means of numerical simulation. Such impacts include free-stream velocity magnitude, seabed and inflow direction of velocity. The results of the open water performance prediction show that the power output and efficiency of marine current turbine varies from different marine environments. The velocity distribution should be clearly and the suitable unit installation depth and direction be clearly chosen, which can ensure the most effective strategy for energy capture before installing the marine current turbine. The findings of this paper are expected to be beneficial in developing tidal current turbines and array in the future

  14. Using Chemicals to Optimize Conformance Control in Fractured Reservoirs; TOPICAL

    International Nuclear Information System (INIS)

    Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Ananad; Wavrik, Kathryn

    2001-01-01

    This report describes work performed during the third and final year of the project, Using Chemicals to Optimize Conformance Control in Fractured Reservoirs. This research project had three objectives. The first objective was to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective was to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective was to develop procedures to optimize blocking agent placement in naturally fractured reservoirs

  15. Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

    Science.gov (United States)

    Mitchell, Diane Kuhl; Wojciechowski, Josephine; Samms, Charneta

    2012-01-01

    A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

  16. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna's hummingbirds.

    Science.gov (United States)

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-11-19

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability.

  17. Final Report: Development of a Chemical Model to Predict the Interactions between Supercritical CO2, Fluid and Rock in EGS Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    McPherson, Brian J. [University of Utah; Pan, Feng [University of Utah

    2014-09-24

    This report summarizes development of a coupled-process reservoir model for simulating enhanced geothermal systems (EGS) that utilize supercritical carbon dioxide as a working fluid. Specifically, the project team developed an advanced chemical kinetic model for evaluating important processes in EGS reservoirs, such as mineral precipitation and dissolution at elevated temperature and pressure, and for evaluating potential impacts on EGS surface facilities by related chemical processes. We assembled a new database for better-calibrated simulation of water/brine/ rock/CO2 interactions in EGS reservoirs. This database utilizes existing kinetic and other chemical data, and we updated those data to reflect corrections for elevated temperature and pressure conditions of EGS reservoirs.

  18. Development and application of 3-D fractal reservoir model based on collage theorem

    Energy Technology Data Exchange (ETDEWEB)

    Kim, I.K.; Kim, K.S.; Sung, W.M. [Hanyang Univ., Seoul (Korea, Republic of)

    1995-04-30

    Reservoir characterization is the essential process to accurately evaluate the reservoir and has been conducted by geostatistical method, SRA algorithm, and etc. The characterized distribution of heterogeneous property by these methods shows randomly distributed phenomena, and does not present anomalous shape of property variation at discontinued space as compared with the observed shape in nature. This study proposed a new algorithm of fractal concept based on collage theorem, which can virtually present not only geometric shape of irregular and anomalous pore structures or coastlines, but also property variation for discontinuously observed data. With a basis of fractal concept, three dimensional fractal reservoir model was developed to more accurately characterize the heterogeneous reservoir. We performed analysis of pre-predictable hypothetically observed permeability data by using the fractal reservoir model. From the results, we can recognize that permeability distributions in the areal view or the cross-sectional view were consistent with the observed data. (author). 8 refs., 1 tab., 6 figs.

  19. An alternative approach to assessing feasibility of flushing sediment from reservoirs

    Directory of Open Access Journals (Sweden)

    Elfimov Valeriy Ivanovich

    2014-07-01

    Full Text Available Effective parameters on feasibility of sediment flushing through reservoirs include hydrological, hydraulic, and topographic properties of the reservoirs. In this study, the performances of the Decision tree forest (DTF and Group method of data handling (GMDH for assessing feasibility of flushing sediment from reservoirs, were investigated. In this way, Decision tree Forest, that combines multiple Decision tree, used to evaluate the relative importance of factors affecting flushing sediment. At the second step, GMDH deployed to predict the feasibility of flushing sediment from reservoirs. Results indicate that these models, as an efficient novel approach with an acceptable range of error, can be used successfully for assessing feasibility of flushing sediment from reservoirs.

  20. Predicting students' intention to use stimulants for academic performance enhancement.

    Science.gov (United States)

    Ponnet, Koen; Wouters, Edwin; Walrave, Michel; Heirman, Wannes; Van Hal, Guido

    2015-02-01

    The non-medical use of stimulants for academic performance enhancement is becoming a more common practice among college and university students. The objective of this study is to gain a better understanding of students' intention to use stimulant medication for the purpose of enhancing their academic performance. Based on an extended model of Ajzen's theory of planned behavior, we examined the predictive value of attitude, subjective norm, perceived behavioral control, psychological distress, procrastination, substance use, and alcohol use on students' intention to use stimulants to improve their academic performance. The sample consisted of 3,589 Flemish university and college students (mean age: 21.59, SD: 4.09), who participated anonymously in an online survey conducted in March and April 2013. Structural equation modeling was used to investigate the relationships among the study variables. Our results indicate that subjective norm is the strongest predictor of students' intention to use stimulant medication, followed by attitude and perceived behavioral control. To a lesser extent, procrastinating tendencies, psychological distress, and substance abuse contribute to students' intention. Conclusions/ Importance: Based on these findings, we provide several recommendations on how to curtail students' intention to use stimulant medication for the purpose of improving their academic performance. In addition, we urge researchers to identify other psychological variables that might be related to students' intention.

  1. Near peripheral motion contrast threshold predicts older drivers' simulator performance.

    Science.gov (United States)

    Henderson, Steven; Gagnon, Sylvain; Collin, Charles; Tabone, Ricardo; Stinchcombe, Arne

    2013-01-01

    Our group has previously demonstrated that peripheral motion contrast threshold (PMCT) is significantly associated with self-reported accident risk of older drivers (questionnaire assessment), and with Useful Field of View(®) subtest 2 (UFOV2). It has not been shown, however, that PMCT is significantly associated with driving performance. Using the method of descending limits (spatial two-alternative forced choice) we assessed motion contrast thresholds of 28 young participants (25-45), and 21 older drivers (63-86) for 0.4 cycle/degree drifting Gabor stimuli at 15° eccentricity and examined whether it was related to performance on a simulated on-road test and to a measure of visual attention (UFOV(®) subtests 2 and 3). Peripheral motion contrast thresholds (PMCT) of younger participants were significantly lower than older participants. PMCT and UFOV2 significantly predicted driving examiners' scores of older drivers' simulator performance, as well as number of crashes. Within the older group, PMCT correlated significantly with UFOV2, UFOV3, and age. Within the younger group, PMCT was not significantly related to either UFOV(®) scores or age. Partial correlations showed that: substantial association between PMCT and UFOV2 was not age-related (within the older driver group); PMCT and UFOV2 tapped a common visual function; and PMCT assessed a component not captured by UFOV2. PMCT is potentially a useful assessment tool for predicting accident risk of older drivers, and for informing efforts to develop effective countermeasures to remediate this functional deficit as much as possible. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Performance analysis and comparison of an Atkinson cycle coupled to variable temperature heat reservoirs under maximum power and maximum power density conditions

    International Nuclear Information System (INIS)

    Wang, P.-Y.; Hou, S.-S.

    2005-01-01

    In this paper, performance analysis and comparison based on the maximum power and maximum power density conditions have been conducted for an Atkinson cycle coupled to variable temperature heat reservoirs. The Atkinson cycle is internally reversible but externally irreversible, since there is external irreversibility of heat transfer during the processes of constant volume heat addition and constant pressure heat rejection. This study is based purely on classical thermodynamic analysis methodology. It should be especially emphasized that all the results and conclusions are based on classical thermodynamics. The power density, defined as the ratio of power output to maximum specific volume in the cycle, is taken as the optimization objective because it considers the effects of engine size as related to investment cost. The results show that an engine design based on maximum power density with constant effectiveness of the hot and cold side heat exchangers or constant inlet temperature ratio of the heat reservoirs will have smaller size but higher efficiency, compression ratio, expansion ratio and maximum temperature than one based on maximum power. From the view points of engine size and thermal efficiency, an engine design based on maximum power density is better than one based on maximum power conditions. However, due to the higher compression ratio and maximum temperature in the cycle, an engine design based on maximum power density conditions requires tougher materials for engine construction than one based on maximum power conditions

  3. Performance analysis of tracked panel according to predicted global radiation

    International Nuclear Information System (INIS)

    Chang, T.P.

    2009-01-01

    In this paper, the performance of a south facing single-axis tracked panel was analyzed according to global radiation predicted by empirical model. Mathematic expressions appropriate for single-axis tracking system were derived to calculate the radiation on it. Instantaneous increments of solar energy collected by the tracked panel relative to fixed panel are illustrated. The validity of the empirical model to Taiwan area will also be examined with the actual irradiation data observed in Taipei. The results are summarized as follows: the gains made by the tracked panel relative to a fixed panel are between 20.0% and 33.9% for four specified days of year, between 20.9% and 33.2% for the four seasons and 27.6% over the entire year. For latitudes below 65 deg., the yearly optimal tilt angle of a fixed panel is close to 0.8 times latitude, the irradiation ratio of the tracked panel to the fixed panel is about 1.3, which are smaller than the corresponding values calculated from extraterrestrial radiation, suggesting us that the installation angle should be adjusted toward a flatter angle and that the gain of the tracked panel will reduce while it works in cloudy climate or in air pollution environment. Although the captured radiation increases with the maximal rotation angle of panel, but the benefit on the global radiation case is still not so good as that on extraterrestrial radiation case. The irradiation data observed is much less than the data predicted by the empirical model, however the trend of fitting curve to the observed data is somewhat in agreement with that to the predicted one; the yearly gain is 14.3% when a tracked panel is employed throughout the year.

  4. Predictive Performance Tuning of OpenACC Accelerated Applications

    KAUST Repository

    Siddiqui, Shahzeb

    2014-05-04

    Graphics Processing Units (GPUs) are gradually becoming mainstream in supercomputing as their capabilities to significantly accelerate a large spectrum of scientific applications have been clearly identified and proven. Moreover, with the introduction of high level programming models such as OpenACC [1] and OpenMP 4.0 [2], these devices are becoming more accessible and practical to use by a larger scientific community. However, performance optimization of OpenACC accelerated applications usually requires an in-depth knowledge of the hardware and software specifications. We suggest a prediction-based performance tuning mechanism [3] to quickly tune OpenACC parameters for a given application to dynamically adapt to the execution environment on a given system. This approach is applied to a finite difference kernel to tune the OpenACC gang and vector clauses for mapping the compute kernels into the underlying accelerator architecture. Our experiments show a significant performance improvement against the default compiler parameters and a faster tuning by an order of magnitude compared to the brute force search tuning.

  5. Music-related reward responses predict episodic memory performance.

    Science.gov (United States)

    Ferreri, Laura; Rodriguez-Fornells, Antoni

    2017-12-01

    Music represents a special type of reward involving the recruitment of the mesolimbic dopaminergic system. According to recent theories on episodic memory formation, as dopamine strengthens the synaptic potentiation produced by learning, stimuli triggering dopamine release could result in long-term memory improvements. Here, we behaviourally test whether music-related reward responses could modulate episodic memory performance. Thirty participants rated (in terms of arousal, familiarity, emotional valence, and reward) and encoded unfamiliar classical music excerpts. Twenty-four hours later, their episodic memory was tested (old/new recognition and remember/know paradigm). Results revealed an influence of music-related reward responses on memory: excerpts rated as more rewarding were significantly better recognized and remembered. Furthermore, inter-individual differences in the ability to experience musical reward, measured through the Barcelona Music Reward Questionnaire, positively predicted memory performance. Taken together, these findings shed new light on the relationship between music, reward and memory, showing for the first time that music-driven reward responses are directly implicated in higher cognitive functions and can account for individual differences in memory performance.

  6. Application of Machine Learning Algorithms for the Query Performance Prediction

    Directory of Open Access Journals (Sweden)

    MILICEVIC, M.

    2015-08-01

    Full Text Available This paper analyzes the relationship between the system load/throughput and the query response time in a real Online transaction processing (OLTP system environment. Although OLTP systems are characterized by short transactions, which normally entail high availability and consistent short response times, the need for operational reporting may jeopardize these objectives. We suggest a new approach to performance prediction for concurrent database workloads, based on the system state vector which consists of 36 attributes. There is no bias to the importance of certain attributes, but the machine learning methods are used to determine which attributes better describe the behavior of the particular database server and how to model that system. During the learning phase, the system's profile is created using multiple reference queries, which are selected to represent frequent business processes. The possibility of the accurate response time prediction may be a foundation for automated decision-making for database (DB query scheduling. Possible applications of the proposed method include adaptive resource allocation, quality of service (QoS management or real-time dynamic query scheduling (e.g. estimation of the optimal moment for a complex query execution.

  7. Reservoir characterization and final pre-test analysis in support of the compressed-air-energy-storage Pittsfield aquifer field test in Pike County, Illinois

    Energy Technology Data Exchange (ETDEWEB)

    Wiles, L.E.; McCann, R.A.

    1983-06-01

    The work reported is part of a field experimental program to demonstrate and evaluate compressed air energy storage in a porous media aquifer reservoir near Pittsfield, Illinois. The reservoir is described. Numerical modeling of the reservoir was performed concurrently with site development. The numerical models were applied to predict the thermohydraulic performance of the porous media reservoir. This reservoir characterization and pre-test analysis made use of evaluation of bubble development, water coning, thermal development, and near-wellbore desaturation. The work was undertaken to define the time required to develop an air storage bubble of adequate size, to assess the specification of instrumentation and above-ground equipment, and to develop and evaluate operational strategies for air cycling. A parametric analysis was performed for the field test reservoir. (LEW)

  8. Mental Strategies Predict Performance and Satisfaction with Performance among Soccer Players.

    Science.gov (United States)

    Kruk, Magdalena; Blecharz, Jan; Boberska, Monika; Zarychta, Karolina; Luszczynska, Aleksandra

    2017-10-01

    This study investigated the changes in mental strategies across the season and their effects on performance and satisfaction with individual performance. Data were collected three times: at the pre-season at Time 1 (T1; baseline), in the mid-season at Time 2 (T2; two-month follow-up), and at the end-of-season at Time 3 (T3; nine-month follow-up) among male soccer players (N = 97) aged 16-27. Athletes completed the questionnaires assessing the use of nine psychological strategies in competition and the level of satisfaction with individual performance. Endurance performance was measured objectively with a 300 m run. A high level of relaxation (T1) explained better 300 m run performance (T3) and a high level of self-talk explained a higher satisfaction with individual performance (T3). A rare use of distractibility and emotional control (T1) predicted a higher level of satisfaction with individual performance (T3). No predictive role of other psychological strategies was found. The use of emotional control, relaxation, and distractibility increased over the season, whereas the use of imagery and negative thinking declined. Besides the roles of self-talk, imagery, relaxation and goal-setting, the effects of distractibility and emotional control should be taken into account when considering athletes' mental training programs.

  9. Mining Behavior Based Safety Data to Predict Safety Performance

    Energy Technology Data Exchange (ETDEWEB)

    Jeffrey C. Joe

    2010-06-01

    The Idaho National Laboratory (INL) operates a behavior based safety program called Safety Observations Achieve Results (SOAR). This peer-to-peer observation program encourages employees to perform in-field observations of each other's work practices and habits (i.e., behaviors). The underlying premise of conducting these observations is that more serious accidents are prevented from occurring because lower level “at risk” behaviors are identified and corrected before they can propagate into culturally accepted “unsafe” behaviors that result in injuries or fatalities. Although the approach increases employee involvement in safety, the premise of the program has not been subject to sufficient empirical evaluation. The INL now has a significant amount of SOAR data on these lower level “at risk” behaviors. This paper describes the use of data mining techniques to analyze these data to determine whether they can predict if and when a more serious accident will occur.

  10. Prediction in Ungauged Basins (PUB) for estimating water availability during water scarcity conditions: rainfall-runoff modelling of the ungauged diversion inflows to the Ridracoli water supply reservoir

    Science.gov (United States)

    Toth, Elena

    2013-04-01

    The Ridracoli reservoir is the main drinking water supply reservoir serving the whole Romagna region, in Northern Italy. Such water supply system has a crucial role in an area where the different characteristics of the communities to be served, their size, the mass tourism and the presence of food industries highlight strong differences in drinking water needs. Its operation allows high quality drinking water supply to a million resident customers, plus a few millions of tourists during the summer of people and it reduces the need for water pumping from underground sources, and this is particularly important since the coastal area is subject also to subsidence and saline ingression into aquifers. The system experienced water shortage conditions thrice in the last decade, in 2002, in 2007 and in autumn-winter 2011-2012, when the reservoir water storage fell below the attention and the pre-emergency thresholds, thus prompting the implementation of a set of mitigation measures, including limitations to the population's water consumption. The reservoir receives water not only from the headwater catchment, closed at the dam, but also from four diversion watersheds, linked to the reservoir through an underground water channel. Such withdrawals are currently undersized, abstracting only a part of the streamflow exceeding the established minimum flows, due to the design of the water intake structures; it is therefore crucial understanding how the reservoir water availability might be increased through a fuller exploitation of the existing diversion catchment area. Since one of the four diversion catchment is currently ungauged (at least at the fine temporal scale needed for keeping into account the minimum flow requirements downstream of the intakes), the study first presents the set up and parameterisation of a continuous rainfall-runoff model at hourly time-step for the three gauged diversion watersheds and for the headwater catchment: a regional parameterisation

  11. Do Maximal Roller Skiing Speed and Double Poling Performance Predict Youth Cross-Country Skiing Performance?

    Directory of Open Access Journals (Sweden)

    Roland Stöggl, Erich Müller, Thomas Stöggl

    2017-09-01

    Full Text Available The aims of the current study were to analyze whether specific roller skiing tests and cycle length are determinants of youth cross-country (XC skiing performance, and to evaluate sex specific differences by applying non-invasive diagnostics. Forty-nine young XC skiers (33 boys; 13.8 ± 0.6 yrs and 16 girls; 13.4 ± 0.9 yrs performed roller skiing tests consisting of both shorter (50 m and longer durations (575 m. Test results were correlated with on snow XC skiing performance (PXC based on 3 skating and 3 classical distance competitions (3 to 6 km. The main findings of the current study were: 1 Anthropometrics and maturity status were related to boys’, but not to girls’ PXC; 2 Significant moderate to acceptable correlations between girls’ and boys’ short duration maximal roller skiing speed (double poling, V2 skating, leg skating and PXC were found; 3 Boys’ PXC was best predicted by double poling test performance on flat and uphill, while girls’ performance was mainly predicted by uphill double poling test performance; 4 When controlling for maturity offset, boys’ PXC was still highly associated with the roller skiing tests. The use of simple non-invasive roller skiing tests for determination of PXC represents practicable support for ski clubs, schools or skiing federations in the guidance and evaluation of young talent.

  12. Reservoir souring: Problems, uncertainties and modelling. Part I: Problems and uncertainty involved in prediction. Part II: Preliminary investigations of a computational model

    International Nuclear Information System (INIS)

    Paulsen, J.E.; Read, P.A.; Thompson, C.P.; Jelley, C.; Lezeau, P.

    1996-01-01

    The paper relates to improved oil recovery (IOR) techniques by mathematical modelling. The uncertainty involved in modelling of reservoir souring is discussed. IOR processes are speculated to influence a souring process in a positive direction. Most models do not take into account pH in reservoir fluids, and thus do not account for partitioning behaviour of sulfide. Also, sulfide is antagonistic to bacterial metabolism and impedes to bacterial metabolism and impedes the sulfate reduction rate, this may be an important factor in modelling. Biofilms are thought to play a crucial role in a reservoir souring process. Biofilm in a reservoir matrix is different from biofilm in open systems. This has major impact on microbial impact on microbial transport and behaviour. Studies on microbial activity in reservoir matrices must be carried out with model cores, in order to mimic a realistic situation. Sufficient data do not exist today. The main conclusion is that a model does not reflect a true situation before the nature of these elements is understood. A simplified version of an Norwegian developed biofilm model is discussed. The model incorporates all the important physical phenomena studied in the above references such as bacteria growth limited by nutrients and/or energy sources and hydrogen sulfide adsorption. 18 refs., 8 figs., 1 tab

  13. Reservoir souring: Problems, uncertainties and modelling. Part I: Problems and uncertainty involved in prediction. Part II: Preliminary investigations of a computational model

    Energy Technology Data Exchange (ETDEWEB)

    Paulsen, J.E. [Rogalandsforskning, Stavanger (Norway); Read, P.A.; Thompson, C.P.; Jelley, C.; Lezeau, P.

    1996-12-31

    The paper relates to improved oil recovery (IOR) techniques by mathematical modelling. The uncertainty involved in modelling of reservoir souring is discussed. IOR processes are speculated to influence a souring process in a positive direction. Most models do not take into account pH in reservoir fluids, and thus do not account for partitioning behaviour of sulfide. Also, sulfide is antagonistic to bacterial metabolism and impedes to bacterial metabolism and impedes the sulfate reduction rate, this may be an important factor in modelling. Biofilms are thought to play a crucial role in a reservoir souring process. Biofilm in a reservoir matrix is different from biofilm in open systems. This has major impact on microbial impact on microbial transport and behaviour. Studies on microbial activity in reservoir matrices must be carried out with model cores, in order to mimic a realistic situation. Sufficient data do not exist today. The main conclusion is that a model does not reflect a true situation before the nature of these elements is understood. A simplified version of an Norwegian developed biofilm model is discussed. The model incorporates all the important physical phenomena studied in the above references such as bacteria growth limited by nutrients and/or energy sources and hydrogen sulfide adsorption. 18 refs., 8 figs., 1 tab.

  14. Performance prediction of hot mix asphalt from asphalt binders

    International Nuclear Information System (INIS)

    Hafeez, I.; Kamal, M.A.; Shahzad, Q.; Bashir, N.; Ahadi, M.R.

    2012-01-01

    Asphalt binder being a high weight hydrocarbon contains asphaltene and maltene and is widely used as cementing materials in the construction of flexible pavements. Its performance in hot mix asphalt also depends on combining with different proportions of aggregates. The main objective of this study was to characterize asphalt cement rheological behavior and to investigate the influence of asphalt on asphalt-aggregate mixtures prepared with virgin binders and using polymers. Binder rheology and mixtures stiffness were determined under a range of cyclic loadings and temperature conditions. Master curves were developed for the evaluation of relationship between parameters like complex modulus and phase angle at different frequencies. Horizontal shift factors were also computed to determine time and temperature response of binders and mixes. The results showed that the stiffness of both the binder and the mixes depends on temperature and frequency of load. Polymer modified binder is least susceptible to temperature variations as compared to other virgin asphalt cement. Performance of asphalt mixtures can be predicted from those of asphalt binders using the master curve technique. (author)

  15. Preparatory neural activity predicts performance on a conflict task.

    Science.gov (United States)

    Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

    2007-10-24

    Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

  16. Further developments in performance prediction techniques of adiabatic diesel engines

    Energy Technology Data Exchange (ETDEWEB)

    Rasihhan, Y

    1990-01-01

    The engine cycle simulation program 'SPICE', developed at Bath University, has been used extensively for insulated diesel engine research. The present study introduces more comprehensive engine heat transfer models thus enabling us to study the insulated engine heat transfer and performance characteristics in more detail. The new version of 'SPICE' separates the gas to wall heat transfer into two parts, convective and radiative. For this purpose, a detailed radiative heat transfer model which considers both the flame (gas and soot) and wall to wall radiative heat transfer is written. The previous engine resistance model is refined and replaced by a more detailed resistance model which considers piston-liner conduction heat transfer and 2-D heat flow in the liner. The wall surface temperature swing is also included in the engine heat transfer calculations which is quite significant in low conductivity ceramic insulated engines. A 1-D finite difference model is written for the transient heat transfer region of the wall and linked to the engine resistance model. This new version of 'SPICE' is used to predict the insulated engine heat transfer and performance for the experimental Petter PH1W engine for various insulation levels and schemes. An answer to the controversy of increase in engine heat loss with insulation is looked for. The effect of wall deposits on engine heat transfer and its significance for the insulated engine is highlighted. (Author).

  17. PREDICTING THERMAL PERFORMANCE OF ROOFING SYSTEMS IN SURABAYA

    Directory of Open Access Journals (Sweden)

    MINTOROGO Danny Santoso

    2015-07-01

    Full Text Available Traditional roofing systems in the developing country likes Indonesia are still be dominated by the 30o, 45o, and more pitched angle roofs; the roofing cover materials are widely used to traditional clay roof tiles, then modern concrete roof tiles, and ceramic roof tiles. In the 90’s decay, shop houses are prosperous built with flat concrete roofs dominant. Green roofs and roof ponds are almost rarely built to meet the sustainable environmental issues. Some tested various roof systems in Surabaya were carried out to observe the roof thermal performances. Mathematical equation model from three references are also performed in order to compare with the real project tested. Calculated with equation (Kabre et al., the 30o pitched concrete-roof-tile, 30o clay-roof-tile, 45o pitched concrete-roof-tile are the worst thermal heat flux coming to room respectively. In contrast, the bare soil concrete roof and roof pond system are the least heat flux streamed onto room. Based on predicted calculation without insulation and cross-ventilation attic space, the roof pond and bare soil concrete roof (greenery roof are the appropriate roof systems for the Surabaya’s climate; meanwhile the most un-recommended roof is pitched 30o or 45o angle with concrete-roof tiles roofing systems.

  18. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    International Nuclear Information System (INIS)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development

  19. Exploration of Machine Learning Approaches to Predict Pavement Performance

    Science.gov (United States)

    2018-03-23

    Machine learning (ML) techniques were used to model and predict pavement condition index (PCI) for various pavement types using a variety of input variables. The primary objective of this research was to develop and assess PCI predictive models for t...

  20. Gaussian Process Regression for WDM System Performance Prediction

    DEFF Research Database (Denmark)

    Wass, Jesper; Thrane, Jakob; Piels, Molly

    2017-01-01

    Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.......Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data....

  1. Does Residency Selection Criteria Predict Performance in Orthopaedic Surgery Residency?

    Science.gov (United States)

    Raman, Tina; Alrabaa, Rami George; Sood, Amit; Maloof, Paul; Benevenia, Joseph; Berberian, Wayne

    2016-04-01

    More than 1000 candidates applied for orthopaedic residency positions in 2014, and the competition is intense; approximately one-third of the candidates failed to secure a position in the match. However, the criteria used in the selection process often are subjective and studies have differed in terms of which criteria predict either objective measures or subjective ratings of resident performance by faculty. Do preresidency selection factors serve as predictors of success in residency? Specifically, we asked which preresidency selection factors are associated or correlated with (1) objective measures of resident knowledge and performance; and (2) subjective ratings by faculty. Charts of 60 orthopaedic residents from our institution were reviewed. Preresidency selection criteria examined included United States Medical Licensing Examination (USMLE) Step 1 and Step 2 scores, Medical College Admission Test (MCAT) scores, number of clinical clerkship honors, number of letters of recommendation, number of away rotations, Alpha Omega Alpha (AOA) honor medical society membership, fourth-year subinternship at our institution, and number of publications. Resident performance was assessed using objective measures including American Board of Orthopaedic Surgery (ABOS) Part I scores and Orthopaedics In-Training Exam (OITE) scores and subjective ratings by faculty including global evaluation scores and faculty rankings of residents. We tested associations between preresidency criteria and the subsequent objective and subjective metrics using linear correlation analysis and Mann-Whitney tests when appropriate. Objective measures of resident performance namely, ABOS Part I scores, had a moderate linear correlation with the USMLE Step 2 scores (r = 0.55, p communication skills" subsection of the global evaluations. We found that USMLE Step 2, number of honors in medical school clerkships, and AOA membership demonstrated the strongest correlations with resident performance. Our

  2. Climbing fibers predict movement kinematics and performance errors.

    Science.gov (United States)

    Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

    2017-09-01

    Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each

  3. Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

    2018-05-01

    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

  4. Frontoparietal white matter integrity predicts haptic performance in chronic stroke

    Directory of Open Access Journals (Sweden)

    Alexandra L. Borstad

    2016-01-01

    . Age strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T–M1 MD and affected hand HASTe score (r = −0.62, p = 0.006 and less affected hand HASTe score (r = −0.53, p = 0.022. Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T–M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  5. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    Science.gov (United States)

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T-M1 MD and affected hand HASTe score (r = - 0.62, p = 0.006) and less affected hand HASTe score (r = - 0.53, p = 0.022). Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD) in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T-M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  6. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna’s hummingbirds

    Science.gov (United States)

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-01-01

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability. DOI: http://dx.doi.org/10.7554/eLife.11159.001 PMID:26583753

  7. Prediction of mandibular rotation: an empirical test of clinician performance.

    Science.gov (United States)

    Baumrind, S; Korn, E L; West, E E

    1984-11-01

    An experiment was conducted in an attempt to determine empirically how effective a number of expert clinicians were at differentiating "backward rotators" from "forward rotators" on the basis of head-film information which might reasonably have been available to them prior to instituting treatment for the correction of Class II malocclusion. As a result of a previously reported ongoing study, pre- and posttreatment head films were available for 188 patients treated in the mixed dentition for the correction of Class II malocclusion and for 50 untreated Class II subjects. These subjects were divided into 14 groups (average size of group, 17; range, 6 to 23) solely on the basis of type of treatment and the clinician from whose clinic the records had originated. From within each group, we selected the two or three subjects who had exhibited the most extreme backward rotation and the two or three subjects who had exhibited the most extreme forward rotation of the mandible during the interval between films. The sole criterion for classification was magnitude of change in the mandibular plane angle of Downs between the pre- and posttreatment films of each patient. The resulting sample contained 32 backward-rotator subjects and 32 forward-rotator subjects. Five expert judges (mean clinical experience, 28 years) were asked to identify the backward-rotator subjects by examination of the pretreatment films. The findings may be summarized as follows: (1) No judge performed significantly better than chance. (2) There was strong evidence that the judges used a shared, though relatively ineffective, set of rules in making their discriminations between forward and backward rotators. (3) Statistical analysis of the predictive power of a set of standard cephalometric measurements which had previously been made for this set of subjects indicated that the numerical data also failed to identify potential backward rotators at a rate significantly better than chance. We infer from these

  8. From obc seismic to porosity volume: A pre-stack analysis of a turbidite reservoir, deepwater Campos Basin, Brazil

    Science.gov (United States)

    Martins, Luiz M. R.

    The Campos Basin is the best known and most productive of the Brazilian coastal basins. Turbidites are, by far, the main oil-bearing reservoirs. Using a four component (4-C) ocean-bottom-cable (OBC) seismic survey I set out to improve the reservoir characterization in a deep-water turbidite field in the Campos Basin. In order to achieve my goal, pre-stack angle gathers were derived and PP and PS inversion were performed. The inversion was used as an input to predict the petrophysical properties of the reservoir. Converting seismic reflection amplitudes into impedance profiles not only maximizes vertical resolution but also minimizes tuning effects. Mapping the porosity is extremely important in the development of a hydrocarbon reservoirs. Combining seismic attributes derived from the P-P data and porosity logs I use linear multi-regression and neural network geostatistical tools to predict porosity between the seismic attributes and porosity logs at the well locations. After predicting porosity in well locations, those relationships were applied to the seismic attributes to generate a 3-D porosity volume. The predicted porosity volume highlighted the best reservoir facies in the reservoir. The integration of elastic impedance, shear impedance and porosity improved the reservoir characterization.

  9. Data Integration for the Generation of High Resolution Reservoir Models

    Energy Technology Data Exchange (ETDEWEB)

    Albert Reynolds; Dean Oliver; Gaoming Li; Yong Zhao; Chaohui Che; Kai Zhang; Yannong Dong; Chinedu Abgalaka; Mei Han

    2009-01-07

    The goal of this three-year project was to develop a theoretical basis and practical technology for the integration of geologic, production and time-lapse seismic data in a way that makes best use of the information for reservoir description and reservoir performance predictions. The methodology and practical tools for data integration that were developed in this research project have been incorporated into computational algorithms that are feasible for large scale reservoir simulation models. As the integration of production and seismic data require calibrating geological/geostatistical models to these data sets, the main computational tool is an automatic history matching algorithm. The following specific goals were accomplished during this research. (1) We developed algorithms for calibrating the location of the boundaries of geologic facies and the distribution of rock properties so that production and time-lapse seismic data are honored. (2) We developed and implemented specific procedures for conditioning reservoir models to time-lapse seismic data. (3) We developed and implemented algorithms for the characterization of measurement errors which are needed to determine the relative weights of data when conditioning reservoir models to production and time-lapse seismic data by automatic history matching. (4) We developed and implemented algorithms for the adjustment of relative permeability curves during the history matching process. (5) We developed algorithms for production optimization which accounts for geological uncertainty within the context of closed-loop reservoir management. (6) To ensure the research results will lead to practical public tools for independent oil companies, as part of the project we built a graphical user interface for the reservoir simulator and history matching software using Visual Basic.

  10. MHA admission criteria and program performance: do they predict career performance?

    Science.gov (United States)

    Porter, J; Galfano, V J

    1987-01-01

    The purpose of this study was to determine to what extent admission criteria predict graduate school and career performance. The study also analyzed which objective and subjective criteria served as the best predictors. MHA graduates of the University of Minnesota from 1974 to 1977 were surveyed to assess career performance. Student files served as the data base on admission criteria and program performance. Career performance was measured by four variables: total compensation, satisfaction, fiscal responsibility, and level of authority. High levels of MHA program performance were associated with women who had high undergraduate GPAs from highly selective undergraduate colleges, were undergraduate business majors, and participated in extracurricular activities. High levels of compensation were associated with relatively low undergraduate GPAs, high levels of participation in undergraduate extracurricular activities, and being single at admission to graduate school. Admission to MHA programs should be based upon both objective and subjective criteria. Emphasis should be placed upon the selection process for MHA students since admission criteria are shown to explain 30 percent of the variability in graduate program performance, and as much as 65 percent of the variance in level of position authority.

  11. Evaluation of the hydraulic and biological performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, 2014

    Science.gov (United States)

    Beeman, John W.; Evans, Scott D.; Haner, Philip V.; Hansel, Hal C.; Hansen, Amy C.; Hansen, Gabriel S.; Hatton, Tyson W.; Sprando, Jamie M.; Smith, Collin D.; Adams, Noah S.

    2016-01-12

    The biological and hydraulic performance of a new portable floating fish collector (PFFC) located in a cul-de-sac within the forebay of Cougar Dam, Oregon, was evaluated during 2014. The purpose of the PFFC was to explore surface collection as a means to capture juvenile salmonids at one or more sites using a small, cost-effective, pilot-scale device. The PFFC used internal pumps to draw attraction flow over an inclined plane about 3 meters (m) deep, through a flume at a design velocity of as much as 6 feet per second (ft/s), and to empty a small amount of water and any entrained fish into a collection box. Performance of the PFFC was evaluated at 64 cubic feet per second (ft3/s) (Low) and 109 ft3/s (High) inflow rates alternated using a randomized-block schedule from May 27 to December 16, 2014. The evaluation of the biological performance was based on trap catch; behaviors, locations, and collection of juvenile Chinook salmon (Oncorhynchus tshawytscha) tagged with acoustic transmitters plus passive integrated transponder (PIT) tags; collection of juvenile Chinook salmon implanted with only PIT tags; and untagged fish monitored near and within the PFFC using acoustic cameras. The evaluation of hydraulic performance was based on measurements of water velocity and direction of flow in the PFFC.

  12. Daily reservoir inflow forecasting combining QPF into ANNs model

    Science.gov (United States)

    Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

    2009-01-01

    Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

  13. Multilevel techniques for Reservoir Simulation

    DEFF Research Database (Denmark)

    Christensen, Max la Cour

    The subject of this thesis is the development, application and study of novel multilevel methods for the acceleration and improvement of reservoir simulation techniques. The motivation for addressing this topic is a need for more accurate predictions of porous media flow and the ability to carry...... Full Approximation Scheme) • Variational (Galerkin) upscaling • Linear solvers and preconditioners First, a nonlinear multigrid scheme in the form of the Full Approximation Scheme (FAS) is implemented and studied for a 3D three-phase compressible rock/fluids immiscible reservoir simulator...... is extended to include a hybrid strategy, where FAS is combined with Newton’s method to construct a multilevel nonlinear preconditioner. This method demonstrates high efficiency and robustness. Second, an improved IMPES formulated reservoir simulator is implemented using a novel variational upscaling approach...

  14. Estimation of Bank Erosion Due To Reservoir Operation in Cascade (Case Study: Citarum Cascade Reservoir

    Directory of Open Access Journals (Sweden)

    Sri Legowo

    2009-11-01

    Full Text Available Sedimentation is such a crucial issue to be noted once the accumulated sediment begins to fill the reservoir dead storage, this will then influence the long-term reservoir operation. The sediment accumulated requires a serious attention for it may influence the storage capacity and other reservoir management of activities. The continuous inflow of sediment to the reservoir will decrease the capacity of reservoir storage, the reservoir value in use, and the useful age of reservoir. Because of that, the rate of the sediment needs to be delayed as possible. In this research, the delay of the sediment rate is considered based on the rate of flow of landslide of the reservoir slope. The rate of flow of the sliding slope can be minimized by way of each reservoir autonomous efforts. This effort can be performed through; the regulation of fluctuating rate of reservoir surface current that does not cause suddenly drawdown and upraising as well. The research model is compiled using the searching technique of Non Linear Programming (NLP.The rate of bank erosion for the reservoir variates from 0.0009 to 0.0048 MCM/year, which is no sigrificant value to threaten the life time of reservoir.Mean while the rate of watershed sediment has a significant value, i.e: 3,02 MCM/year for Saguling that causes to fullfill the storage capacity in 40 next years (from years 2008.

  15. A comparison between the pressure-lag model and the rate-type model for the prediction of reservoir compaction and surface subsidence

    Energy Technology Data Exchange (ETDEWEB)

    Smits, R.M.M.; De Waal, J.A.

    1988-06-01

    A theoretical study has been carried out to investigate whether the nonlinear compaction behavior of sandstone reservoirs, which has been reported for most well-documented field cases, can be explained by pressure lags in interbedding and/or neighboring low-permeability (shale) layers. On the basis of the results obtained, it is concluded that pressure-lag effects in normally encountered production scenarios cannot account for these nonlinearities, even under worst-case conditions. Therefore, the nonlinear field-compaction behavior must be caused by rate effects in the sandstone reservoir rock itself. This is supported by the fact that a rate-type compaction model recently introduced does indeed give a good description of the observed field behavior.

  16. Understanding the True Stimulated Reservoir Volume in Shale Reservoirs

    KAUST Repository

    Hussain, Maaruf

    2017-06-06

    Successful exploitation of shale reservoirs largely depends on the effectiveness of hydraulic fracturing stimulation program. Favorable results have been attributed to intersection and reactivation of pre-existing fractures by hydraulically-induced fractures that connect the wellbore to a larger fracture surface area within the reservoir rock volume. Thus, accurate estimation of the stimulated reservoir volume (SRV) becomes critical for the reservoir performance simulation and production analysis. Micro-seismic events (MS) have been commonly used as a proxy to map out the SRV geometry, which could be erroneous because not all MS events are related to hydraulic fracture propagation. The case studies discussed here utilized a fully 3-D simulation approach to estimate the SRV. The simulation approach presented in this paper takes into account the real-time changes in the reservoir\\'s geomechanics as a function of fluid pressures. It is consisted of four separate coupled modules: geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive re-meshing. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Our simulations were run on a Cray XC-40 HPC system. The studies outcomes proved the approach of using MS data as a proxy for SRV to be significantly flawed. Many of the observed stimulated natural fractures are stress related and very few that are closer to the injection field are connected. The situation is worsened in a highly laminated shale reservoir as the hydraulic fracture propagation is significantly hampered. High contrast in the in-situ stresses related strike-slip developed thereby shortens the extent of SRV. However, far field nature fractures that were not connected to

  17. A unique application of the instream flow incremental methodology (IFIM) to predict impacts on riverine aquatic habitat, resulting from construction of a proposed hydropower reservoir

    International Nuclear Information System (INIS)

    Foote, P.S.

    1999-01-01

    The City of Harrisburg, Pennsylvania, proposed to construct a new low-head hydroelectric project on the Susquehanna River in the central part of the state in 1986, about 108 km upstream of the river mouth. As part of the licensing process, the city was required by the Federal Energy Regulatory Commission to carry out studies that would forecast the impacts on riverine aquatic habitat as a result of construction of the proposed 13 km long by 1.5 km wide reservoir. The methodology selected by the city and its consultants was to use the IFIM to model the habitat conditions in the project reach both before and after construction of the proposed reservoir.The IFIM is usually used to model instream flow releases downstream of dams and diversions, and had not been used before to model habitat conditions within the proposed reservoir area. The study team hydraulically modelled the project reach using existing hydraulic data, and a HEC-2 backwater analysis to determine post-project water surface elevations. The IFG-4 model was used to simulate both pre- and post-project water velocities, by distributing velocities across transects based on known discharges and cell depth. Effects on aquatic habitat were determined using the IFIM PHABSIM program, in which criteria for several evaluation species and life stages were used to yield estimates of Weighted Usable Area. The analysis showed, based on trends in WUA from pre- and post-project conditions, that habitat conditions would improve for several species and life stages, and would be negatively affected for fewer life stages and species. Some agency concerns that construction of the proposed reservoir would have significant adverse effects on the resident and anadromous fish populations were responded to using these results

  18. Assessing Prediction Performance of Neoadjuvant Chemotherapy Response in Bladder Cancer

    OpenAIRE

    Cremer, Chris

    2016-01-01

    Neoadjuvant chemotherapy is a treatment routinely prescribed to patients diagnosed with muscle-invasive bladder cancer. Unfortunately, not all patients are responsive to this treatment and would greatly benefit from an accurate prediction of their expected response to chemotherapy. In this project, I attempt to develop a model that will predict response using tumour microarray data. I show that using my dataset, every method is insufficient at accurately classifying responders and non-respond...

  19. Prediction of long-term influence of ONKALO and Korvensuo reservoir on groundwater level and water balance components on Olkiluoto island

    International Nuclear Information System (INIS)

    Karvonen, T.

    2010-08-01

    The Olkiluoto surface hydrological model was used to compute the influence of various ONKALO leakage scenarios on changes in groundwater level in overburden soils and hydraulic heads in the bedrock. Moreover, the model effect of ONKALO leakages on water balance components of the Olkiluoto Island (runoff, evapotranspiration, discharge to the sea area through the bedrock and discharge from the Korvensuo reservoir) and on the thickness and area of unsaturated bedrock layer were computed. Leakages into ONKALO lower the groundwater level in overburden soils especially during those years when precipitation is smaller than the long-term average value 550 mm a -1 . According to model results groundwater level can be below sea level if leakage rate into ONKALO is 180 l/min or more. If leakage rate is smaller than 180 l/min groundwater level is above sea level all the time also during dry years. The modelling results show that there are local water divides inside the island both on the southern and northern side of ONKALO at all time points and for all leakage rates. The local water divides ensure that sea water cannot intrude to ONKALO via surface waters. A more detailed version of the Olkiluoto surface hydrological model was developed for the area around the infiltration experiment. Site scale data were available for the location of the most transmissive hydrogeological zones. The analysis of hydraulic responses has shown that there are local connections between different areas around the pumping drillhole OL-KR14. The importance of the local responses was verified by an additional small hydrogeological zone HZInf connecting HZ19A, HZ19C, OL-KR14, OL-PP66, OL-PP68 and OL-PP69 that was added to the model. In future studies it is necessary to describe the local zones explicitly in the model to allow more realistic flow simulations. Discharge has been measured manually in four measuring weirs since March 2003. The old V-shaped measuring weirs were replaced by new automatic

  20. The integrated feasibility analysis of water reuse management in the petroleum exploration performances of unconventional shale reservoirs

    Science.gov (United States)

    Davarpanah, Afshin

    2018-05-01

    Regarding the dramatic increase of water additional resource administration in numerous drilling industries' operational performances and oil/gas extractions, water supply plays a significant role in their performances as efficient as optimum operations, in respect of the way, this utilization is often invisible to the public eye. The necessity of water in a wide variety of drilling operation due to its vast applicant in several functions is widely reported in the literature that has been required to remain these procedures plateau. The objective of this comprehensive study is to conduct an investigation into the studied field and analyze the assessment of necessary water and produced water which is provided in the surface for reinjection procedures in the hydraulic fracturing and water injectivity; in respect of the way, petroleum and drilling industries will push themselves into limits to find suitable water sources from a local source to encapsulate their economic prosperities and virtually eliminate extra expenditures. In comparison to other industries and consumers, oil and gas development is not a significant water consumer, and its water demands can exert profound impacts on local water resources, and this is why it imposes particular challenges among water users in a vast majority of fields and areas in times of drought. Moreover, water has become an increasingly scarce and costly commodity over the past decades, and operators are being beneficially noted that awareness of recycling and reusing phenomenon that has treated effluent is both costs competent and socially responsible. Consequently, energy, environmental situation, and economic prosperity considerations should be analytically and preferably investigated to cover every eventuality and each possibility of disposal and water reuse options.

  1. SILTATION IN RESERVOIRS

    African Journals Online (AJOL)

    Keywords: reservoir model, siltation, sediment, catchment, sediment transport. 1. Introduction. Sediment ... rendered water storage structures useless in less than 25 years. ... reservoir, thus reducing the space available for water storage and ...

  2. Reservoir fisheries of Asia

    International Nuclear Information System (INIS)

    Silva, S.S. De.

    1990-01-01

    At a workshop on reservoir fisheries research, papers were presented on the limnology of reservoirs, the changes that follow impoundment, fisheries management and modelling, and fish culture techniques. Separate abstracts have been prepared for three papers from this workshop

  3. Data Compression of Hydrocarbon Reservoir Simulation Grids

    KAUST Repository

    Chavez, Gustavo Ivan

    2015-05-28

    A dense volumetric grid coming from an oil/gas reservoir simulation output is translated into a compact representation that supports desired features such as interactive visualization, geometric continuity, color mapping and quad representation. A set of four control curves per layer results from processing the grid data, and a complete set of these 3-dimensional surfaces represents the complete volume data and can map reservoir properties of interest to analysts. The processing results yield a representation of reservoir simulation results which has reduced data storage requirements and permits quick performance interaction between reservoir analysts and the simulation data. The degree of reservoir grid compression can be selected according to the quality required, by adjusting for different thresholds, such as approximation error and level of detail. The processions results are of potential benefit in applications such as interactive rendering, data compression, and in-situ visualization of large-scale oil/gas reservoir simulations.

  4. Reservoir characterization of the Upper Jurassic geothermal target formations (Molasse Basin, Germany): role of thermofacies as exploration tool

    Science.gov (United States)

    Homuth, S.; Götz, A. E.; Sass, I.

    2015-06-01

    The Upper Jurassic carbonates of the southern German Molasse Basin are the target of numerous geothermal combined heat and power production projects since the year 2000. A production-orientated reservoir characterization is therefore of high economic interest. Outcrop analogue studies enable reservoir property prediction by determination and correlation of lithofacies-related thermo- and petrophysical parameters. A thermofacies classification of the carbonate formations serves to identify heterogeneities and production zones. The hydraulic conductivity is mainly controlled by tectonic structures and karstification, whilst the type and grade of karstification is facies related. The rock permeability has only a minor effect on the reservoir's sustainability. Physical parameters determined on oven-dried samples have to be corrected, applying reservoir transfer models to water-saturated reservoir conditions. To validate these calculated parameters, a Thermo-Triaxial-Cell simulating the temperature and pressure conditions of the reservoir is used and calorimetric and thermal conductivity measurements under elevated temperature conditions are performed. Additionally, core and cutting material from a 1600 m deep research drilling and a 4850 m (total vertical depth, measured depth: 6020 m) deep well is used to validate the reservoir property predictions. Under reservoir conditions a decrease in permeability of 2-3 magnitudes is observed due to the thermal expansion of the rock matrix. For tight carbonates the matrix permeability is temperature-controlled; the thermophysical matrix parameters are density-controlled. Density increases typically with depth and especially with higher dolomite content. Therefore, thermal conductivity increases; however the dominant factor temperature also decreases the thermal conductivity. Specific heat capacity typically increases with increasing depth and temperature. The lithofacies-related characterization and prediction of reservoir

  5. Stretch due to Penile Prosthesis Reservoir Migration

    Directory of Open Access Journals (Sweden)

    E. Baten

    2016-03-01

    Full Text Available A 43-year old patient presented to the emergency department with stretch, due to impossible deflation of the penile prosthesis, 4 years after successful implant. A CT-scan showed migration of the reservoir to the left rectus abdominis muscle. Refilling of the reservoir was inhibited by muscular compression, causing stretch. Removal and replacement of the reservoir was performed, after which the prosthesis was well-functioning again. Migration of the penile prosthesis reservoir is extremely rare but can cause several complications, such as stretch.

  6. Mathematical and field analysis of longitudinal reservoir infill

    Science.gov (United States)

    Ke, W. T.; Capart, H.

    2016-12-01

    In reservoirs, severe problems are caused by infilled sediment deposits. In long term, the sediment accumulation reduces the capacity of reservoir storage and flood control benefits. In the short term, the sediment deposits influence the intakes of water-supply and hydroelectricity generation. For the management of reservoir, it is important to understand the deposition process and then to predict the sedimentation in reservoir. To investigate the behaviors of sediment deposits, we propose a one-dimensional simplified theory derived by the Exner equation to predict the longitudinal sedimentation distribution in idealized reservoirs. The theory models the reservoir infill geomorphic actions for three scenarios: delta progradation, near-dam bottom deposition, and final infill. These yield three kinds of self-similar analytical solutions for the reservoir bed profiles, under different boundary conditions. Three analytical solutions are composed by error function, complementary error function, and imaginary error function, respectively. The theory is also computed by finite volume method to test the analytical solutions. The theoretical and numerical predictions are in good agreement with one-dimensional small-scale laboratory experiment. As the theory is simple to apply with analytical solutions and numerical computation, we propose some applications to simulate the long-profile evolution of field reservoirs and focus on the infill sediment deposit volume resulting the uplift of near-dam bottom elevation. These field reservoirs introduced here are Wushe Reservoir, Tsengwen Reservoir, Mudan Reservoir in Taiwan, Lago Dos Bocas in Puerto Rico, and Sakuma Dam in Japan.

  7. Sweet spot identification in underexplored shales using multidisciplinary reservoir characterization and key performance indicators : Example of the Posidonia Shale Formation in the Netherlands

    NARCIS (Netherlands)

    Ter Heege, Jan; Zijp, Mart; Nelskamp, Susanne; Douma, Lisanne; Verreussel, Roel; Ten Veen, Johan; de Bruin, Geert; Peters, Rene

    2015-01-01

    Sweet spot identification in underexplored shale gas basins needs to be based on a limited amount of data on shale properties in combination with upfront geological characterization and modelling, because actual production data is usually absent. Multidisciplinary reservoir characterization and

  8. Sweet spot identification in underexplored shales using multidisciplinary reservoir characterization and key performance indicators: example of the Posidonia Shale Formation in the Netherlands

    NARCIS (Netherlands)

    Heege, J.H. ter; Zijp, M.H.A.A.; Nelskamp, S.; Douma, L.A.N.R.; Verreussel, R.M.C.H.; Veen, J.H. ten; Bruin, G. de; Peters, M.C.A.M.

    2015-01-01

    Sweet spot identification in underexplored shale gas basins needs to be based on a limited amount of data on shale properties in combination with upfront geological characterization and modelling, because actual production data is usually absent. Multidisciplinary reservoir characterization and

  9. Reservoir Cathode for Electric Space Propulsion, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose a hollow reservoir cathode to improve performance in ion and Hall thrusters. We will adapt our existing reservoir cathode technology to this purpose....

  10. Texas cracking performance prediction, simulation, and binder recommendation.

    Science.gov (United States)

    2014-10-01

    Recent studies show some mixes with softer binders used outside of Texas (e.g., Minnesotas Cold Weather Road Research Facility mixes) have both good rutting and cracking performance. However, the current binder performance grading (PG) system fail...

  11. Predicting Performance with Contextualized Inventories, No Frame-of-reference Effect?

    NARCIS (Netherlands)

    Holtrop, D.J.; Born, M.P.; de Vries, R.E.

    2014-01-01

    A recent meta-analysis showed that contextualized personality inventories have incremental predictive validity over generic personality inventories when predicting job performance. This study aimed to investigate the differences between two types of contextualization of items: Adding an 'at work'

  12. Architectural Development and Performance Analysis of a Primary Data Cache with Read Miss Address Prediction Capability

    National Research Council Canada - National Science Library

    Christensen, Kathryn

    1998-01-01

    .... The Predictive Read Cache (PRC) further improves the overall memory hierarchy performance by tracking the data read miss patterns of memory accesses, developing a prediction for the next access and prefetching the data into the faster cache memory...

  13. Holland Type as a Moderator of Personality-Performance Predictions.

    Science.gov (United States)

    Fritzsche, Barbara A.; McIntire, Sandra A.; Yost, Amy Powell

    2002-01-01

    Data from 559 undergraduates provided modest evidence that Holland's taxonomy of work environments moderated the relationship between personality and performance. The traits of agreeableness and conscientiousness were better predictors of performance in certain environments. The important relationship between personality and performance may be…

  14. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Directory of Open Access Journals (Sweden)

    Magdalena Ewa Król

    Full Text Available Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  15. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Science.gov (United States)

    Król, Magdalena Ewa; Król, Michał

    2017-01-01

    Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening) content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable) stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  16. Computer Modeling of the Displacement Behavior of Carbon Dioxide in Undersaturated Oil Reservoirs

    Directory of Open Access Journals (Sweden)

    Ju Binshan

    2015-11-01

    Full Text Available The injection of CO2 into oil reservoirs is performed not only to improve oil recovery but also to store CO2 captured from fuel combustion. The objective of this work is to develop a numerical simulator to predict quantitatively supercritical CO2 flooding behaviors for Enhanced Oil Recovery (EOR. A non-isothermal compositional flow mathematical model is developed. The phase transition diagram is designed according to the Minimum Miscibility Pressure (MMP and CO2 maximum solubility in oil phase. The convection and diffusion of CO2 mixtures in multiphase fluids in reservoirs, mass transfer between CO2 and crude and phase partitioning are considered. The governing equations are discretized by applying a fully implicit finite difference technique. Newton-Raphson iterative technique was used to solve the nonlinear equation systems and a simulator was developed. The performances of CO2 immiscible and miscible flooding in oil reservoirs are predicted by the new simulator. The distribution of pressure and temperature, phase saturations, mole fraction of each component in each phase, formation damage caused by asphaltene precipitation and the improved oil recovery are predicted by the simulator. Experimental data validate the developed simulator by comparison with simulation results. The applications of the simulator in prediction of CO2 flooding in oil reservoirs indicate that the simulator is robust for predicting CO2 flooding performance.

  17. Flow Simulation and Performance Prediction of Centrifugal Pumps ...

    African Journals Online (AJOL)

    With the aid of computational fluid dynamics, the complex internal flows in water pump impellers can be well predicted, thus facilitating the product development process of pumps. In this paper a commercial CFD code was used to solve the governing equations of the flow field. A 2-D simulation of turbulent fluid flow is ...

  18. Next-Term Student Performance Prediction: A Recommender Systems Approach

    Science.gov (United States)

    Sweeney, Mack; Rangwala, Huzefa; Lester, Jaime; Johri, Aditya

    2016-01-01

    An enduring issue in higher education is student retention to successful graduation. National statistics indicate that most higher education institutions have four-year degree completion rates around 50%, or just half of their student populations. While there are prediction models which illuminate what factors assist with college student success,…

  19. Predicting Student Performance in a Collaborative Learning Environment

    Science.gov (United States)

    Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

    2015-01-01

    Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

  20. Selection procedures in sports: Improving predictions of athletes’ future performance

    NARCIS (Netherlands)

    den Hartigh, Jan Rudolf; Niessen, Anna; Frencken, Wouter; Meijer, Rob R.

    The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the

  1. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency...

  2. Improving reservoir conformance using gelled polymer systems. Quarterly report, September 25--December 24, 1993

    Energy Technology Data Exchange (ETDEWEB)

    Green, D.W.; Willhite, G.P.; Buller, C.; McCool, S.; Vossoughi, S.; Michnick, M.

    1994-01-19

    The general objectives are to (1) to identify and develop gelled polymer systems which have potential to improve reservoir conformance of fluid displacement processes, (2) to determine the performance of these systems in bulk and in porous media, and (3) to develop methods to predict the capability of these systems to recover oil from petroleum reservoirs. This work focuses on three types of gel systems -- an aqueous polysaccharide (KUSP1) system that gels as a function of pH, the chromium(III)-polyacrylamide system and the aluminum citrate-polyacrylamide system. Laboratory research is directed at the fundamental understanding of the physics and chemistry of the gelation process in bulk form and in porous media. This knowledge will be used to develop conceptual and mathematical models of the gelation process. Mathematical models will then be extended to predict the performance of gelled polymer treatments in oil reservoirs. Results to date are summarized.

  3. Performance of immunological response in predicting virological failure.

    Science.gov (United States)

    Ingole, Nayana; Mehta, Preeti; Pazare, Amar; Paranjpe, Supriya; Sarkate, Purva

    2013-03-01

    In HIV-infected individuals on antiretroviral therapy (ART), the decision on when to switch from first-line to second-line therapy is dictated by treatment failure, and this can be measured in three ways: clinically, immunologically, and virologically. While viral load (VL) decreases and CD4 cell increases typically occur together after starting ART, discordant responses may be seen. Hence the current study was designed to determine the immunological and virological response to ART and to evaluate the utility of immunological response to predict virological failure. All treatment-naive HIV-positive individuals aged >18 years who were eligible for ART were enrolled and assessed at baseline, 6 months, and 12 months clinically and by CD4 cell count and viral load estimations. The patients were categorized as showing concordant favorable (CF), immunological only (IO), virological only (VO), and concordant unfavorable responses (CU). The efficiency of immunological failure to predict virological failure was analyzed across various levels of virological failure (VL>50, >500, and >5,000 copies/ml). At 6 months, 87(79.81%), 7(5.5%), 13 (11.92%), and 2 (1.83%) patients and at 12 months 61(69.3%), 9(10.2%), 16 (18.2%), and 2 (2.3%) patients had CF, IO, VO, and CU responses, respectively. Immunological failure criteria had a very low sensitivity (11.1-40%) and positive predictive value (8.3-25%) to predict virological failure. Immunological criteria do not accurately predict virological failure resulting in significant misclassification of therapeutic responses. There is an urgent need for inclusion of viral load testing in the initiation and monitoring of ART.

  4. Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Daan Nieboer

    Full Text Available External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting.We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1 the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2 the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury.The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples and heterogeneous in scenario 2 (in 17%-39% of simulated samples. Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2.The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

  5. Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

    DEFF Research Database (Denmark)

    Kim, Yohan; Sidney, John; Buus, Søren

    2014-01-01

    Background: It is important to accurately determine the performance of peptide: MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance...... are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last...

  6. Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

  7. Predicting Performance of a Face Recognition System Based on Image Quality

    NARCIS (Netherlands)

    Dutta, A.

    2015-01-01

    In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

  8. Knowledge Tracing and Prediction of Future Trainee Performance

    National Research Council Canada - National Science Library

    Jastrzembski, Tiffany S; Gluck, Kevin A; Gunzelmann, Glenn

    2006-01-01

    ...). This model represents the system's estimate of the student's current knowledge or skill level, established from a performance history. Knowledge tracing (Aleven & Koedinger, 2002; Anderson, Conrad, & Corbett, 1989...

  9. Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

    Directory of Open Access Journals (Sweden)

    Senol Celik

    Full Text Available ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth and testicular (testicular length, scrotal length, and scrotal circumference measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1 and with interaction (MARS_2 terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

  10. Gypsy Field Project in Reservoir Characterization

    International Nuclear Information System (INIS)

    John P. Castagna; William J. Lamb; Carlos Moreno; Roger Young; Lynn Soreghan

    2006-01-01

    The objective of the Gypsy Project was to properly calculate seismic attributes and integrate these into a reservoir characterization project. Significant progress was made on the project in four areas. (1) Attenuation: In order for seismic inversion for rock properties or calculation of seismic attributes used to estimate rock properties to be performed validly, it is necessary to deal with seismic data that has had true amplitude and frequency content restored to account for earth filtering effects that are generally not included in seismic reservoir characterization methodologies. This requires the accurate measurement of seismic attenuation, something that is rarely achieved in practice. It is hoped that such measurements may also provide additional independent seismic attributes for use in reservoir characterization studies. In 2000, we were concerned with the ground truthing of attenuation measurements in the vicinity of wells. Our approach to the problem is one of extracting as time varying wavelet and relating temporal variations in the wavelet to an attenuation model of the earth. This method has the advantage of correcting for temporal variations in the reflectivity spectrum of the earth which confound the spectral ratio methodology which is the most commonly applied means of measuring attenuation from surface seismic data. Part I of the report describes our efforts in seismic attenuation as applied to the Gypsy data. (2) Optimal Attributes: A bewildering array of seismic attributes is available to the reservoir geoscientist to try to establish correlations to rock properties. Ultimately, the use of such a large number of degrees of freedom in the search for correlations with limited well control leads to common misapplication of statistically insignificant results which yields invalid predictions. Cross-validation against unused wells can be used to recognize such problems, but does not offer a solution to the question of which attributes should be used

  11. A unified tool for performance modelling and prediction

    International Nuclear Information System (INIS)

    Gilmore, Stephen; Kloul, Leila

    2005-01-01

    We describe a novel performability modelling approach, which facilitates the efficient solution of performance models extracted from high-level descriptions of systems. The notation which we use for our high-level designs is the Unified Modelling Language (UML) graphical modelling language. The technology which provides the efficient representation capability for the underlying performance model is the multi-terminal binary decision diagram (MTBDD)-based PRISM probabilistic model checker. The UML models are compiled through an intermediate language, the stochastic process algebra PEPA, before translation into MTBDDs for solution. We illustrate our approach on a real-world analysis problem from the domain of mobile telephony

  12. Reservoir model for the Alameda Central waterflood

    Energy Technology Data Exchange (ETDEWEB)

    Randall, T E

    1968-01-01

    The basic approach used in developing the model to characterize the Alameda Central Unit Waterflood assumes continuity of the reservoir mechanics with time. The past performance was analyzed to describe the reservoir and future performance was assumed to follow the established patterns. To develop a mathematical picture of the Alameda Central Unit reservoir, a two-dimensional single-phase steady-state model was used in conjunction with material balance calculations, real-time conversion methods and oil-water interface advance calculations. The model was developed to optimize water injection allocation, determine the configuration of the frontal advance and evaluate the success of the waterflood. The model also provides a basis for continuing review and revision of the basic concepts of reservoir operation. The results of the reservoir study have confirmed the apparent lack of permeability orientation in the pool and indicate that the waterflood is progressing better than originally anticipated.

  13. Prediction of polymer flooding performance using an analytical method

    International Nuclear Information System (INIS)

    Tan Czek Hoong; Mariyamni Awang; Foo Kok Wai

    2001-01-01

    The study investigated the applicability of an analytical method developed by El-Khatib in polymer flooding. Results from a simulator UTCHEM and experiments were compared with the El-Khatib prediction method. In general, by assuming a constant viscosity polymer injection, the method gave much higher recovery values than the simulation runs and the experiments. A modification of the method gave better correlation, albeit only oil production. Investigation is continuing on modifying the method so that a better overall fit can be obtained for polymer flooding. (Author)

  14. IT infrastructure and competitive aggressiveness in explaining and predicting performance

    NARCIS (Netherlands)

    Ajamieh, Aseel; Benitez, Jose; Braojos, Jessica; Gelhard, Carsten Volker

    2016-01-01

    While prior Information Systems and Operations Management literature emphasizes the role of both the firm's IT infrastructure and the general degree of competition as antecedents of firm performance, the organizational capabilities that mediate these important relationships remain undetermined.

  15. Utilizing Lab Tests to Predict Asphalt Concrete Overlay Performance

    Science.gov (United States)

    2017-12-01

    A series of five experimental projects and three demonstration projects were constructed to better understand the performance of pavement overlays using various levels of asphalt binder replacement (ABR) from reclaimed asphalt pavement (RAP), recycle...

  16. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  17. SKread predicts handwriting performance in patients with low vision.

    Science.gov (United States)

    Downes, Ken; Walker, Laura L; Fletcher, Donald C

    2015-06-01

    To assess whether performance on the Smith-Kettlewell Reading (SKread) test is a reliable predictor of handwriting performance in patients with low vision. Cross-sectional study. Sixty-six patients at their initial low-vision rehabilitation evaluation. The patients completed all components of a routine low-vision appointment including logMAR acuity, performed the SKread test, and performed a handwriting task. Patients were timed while performing each task and their accuracy was recorded. The handwriting task was performed by having patients write 5 5-letter words into sets of boxes where each letter is separated by a box. The boxes were 15 × 15 mm, and accuracy was scored with 50 points possible from 25 letters: 1 point for each letter within the confines of a box and 1 point if the letter was legible. Correlation analysis was then performed. Median age of participants was 84 (range 54-97) years. Fifty-seven patients (86%) had age-related macular degeneration or some other maculopathy, whereas 9 patients (14%) had visual impairment from media opacity or neurologic impairment. Median Early Treatment Diabetic Retinopathy Study acuity was 20/133 (range 20/22 to 20/1000), and median logMAR acuity was 0.82 (range 0.04-1.70). SKread errors per block correlated with logMAR acuity (r = 0.6), and SKread time per block correlated with logMAR acuity (r = 0.51). SKread errors per block correlated with handwriting task time/accuracy ratio (r = 0.61). SKread time per block correlated with handwriting task time/accuracy ratio (r = 0.7). LogMAR acuity score correlated with handwriting task time/accuracy ratio (r = 0.42). All p values were handwriting performance in patients with low vision better than logMAR acuity. Copyright © 2015 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

  18. Working memory in children predicts performance on a gambling task.

    Science.gov (United States)

    Audusseau, Jean; Juhel, Jacques

    2015-01-01

    The authors investigated whether working memory (WM) plays a significant role in the development of decision making in children, operationalized by the Children's Gambling Task (CGT). A total of 105 children aged 6-7, 8-9, and 10-11 years old carried out the CGT. Children aged 6-7 years old were found to have a lower performance than older children, which shows that the CGT is sensitive to participant's age. The hypothesis that WM plays a significant role in decision making was then tested following two approaches: (a) an experimental approach, comparing between groups the performance on the CGT in a control condition (the CGT only was administered) to that in a double task condition (participants had to carry out a recall task in addition to the CGT); (b) an interindividual approach, probing the relationship between CGT performance and performance on tasks measuring WM efficiency. The between-groups approach evidenced a better performance in the control group. Moreover, the interindividual approach showed that the higher the participants' WM efficiency was, the higher their performance in the CGT was. Taken together, these two approaches yield converging results that support the hypothesis that WM plays a significant role in decision making in children.

  19. Predicting Subsequent Task Performance From Goal Motivation and Goal Failure

    Directory of Open Access Journals (Sweden)

    Laura Catherine Healy

    2015-07-01

    Full Text Available Recent research has demonstrated that the cognitive processes associated with goal pursuit can continue to interfere with unrelated tasks when a goal is unfulfilled. Drawing from the self-regulation and goal-striving literatures, the present study explored the impact of goal failure on subsequent cognitive and physical task performance. Furthermore, we examined if the autonomous or controlled motivation underpinning goal striving moderates the responses to goal failure. Athletes (75 male, 59 female, Mage = 19.90 years, SDage = 3.50 completed a cycling trial with the goal of covering a given distance in 8 minutes. Prior to the trial, their motivation was primed using a video. During the trial they were provided with manipulated performance feedback, thus creating conditions of goal success or failure. No differences emerged in the responses to goal failure between the primed motivation or performance feedback conditions. We make recommendations for future research into how individuals can deal with failure in goal striving.

  20. Sensorimotor abilities predict on-field performance in professional baseball.

    Science.gov (United States)

    Burris, Kyle; Vittetoe, Kelly; Ramger, Benjamin; Suresh, Sunith; Tokdar, Surya T; Reiter, Jerome P; Appelbaum, L Gregory

    2018-01-08

    Baseball players must be able to see and react in an instant, yet it is hotly debated whether superior performance is associated with superior sensorimotor abilities. In this study, we compare sensorimotor abilities, measured through 8 psychomotor tasks comprising the Nike Sensory Station assessment battery, and game statistics in a sample of 252 professional baseball players to evaluate the links between sensorimotor skills and on-field performance. For this purpose, we develop a series of Bayesian hierarchical latent variable models enabling us to compare statistics across professional baseball leagues. Within this framework, we find that sensorimotor abilities are significant predictors of on-base percentage, walk rate and strikeout rate, accounting for age, position, and league. We find no such relationship for either slugging percentage or fielder-independent pitching. The pattern of results suggests performance contributions from both visual-sensory and visual-motor abilities and indicates that sensorimotor screenings may be useful for player scouting.

  1. Predicted performance of an integrated modular engine system

    Science.gov (United States)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator (ROCETS) program. The nominal steady-state performance is simulated, as well as turbopump thrust chamber and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  2. Methodologies for predicting the part-load performance of aero-derivative gas turbines

    DEFF Research Database (Denmark)

    Haglind, Fredrik; Elmegaard, Brian

    2009-01-01

    Prediction of the part-load performance of gas turbines is advantageous in various applications. Sometimes reasonable part-load performance is sufficient, while in other cases complete agreement with the performance of an existing machine is desirable. This paper is aimed at providing some guidance...... on methodologies for predicting part-load performance of aero-derivative gas turbines. Two different design models – one simple and one more complex – are created. Subsequently, for each of these models, the part-load performance is predicted using component maps and turbine constants, respectively. Comparisons...... with manufacturer data are made. With respect to the design models, the simple model, featuring a compressor, combustor and turbines, results in equally good performance prediction in terms of thermal efficiency and exhaust temperature as does a more complex model. As for part-load predictions, the results suggest...

  3. Performance prediction of industrial centrifuges using scale-down models.

    Science.gov (United States)

    Boychyn, M; Yim, S S S; Bulmer, M; More, J; Bracewell, D G; Hoare, M

    2004-12-01

    Computational fluid dynamics was used to model the high flow forces found in the feed zone of a multichamber-bowl centrifuge and reproduce these in a small, high-speed rotating disc device. Linking the device to scale-down centrifugation, permitted good estimation of the performance of various continuous-flow centrifuges (disc stack, multichamber bowl, CARR Powerfuge) for shear-sensitive protein precipitates. Critically, the ultra scale-down centrifugation process proved to be a much more accurate predictor of production multichamber-bowl performance than was the pilot centrifuge.

  4. Financial performance evaluation and bankruptcy prediction (failure1

    Directory of Open Access Journals (Sweden)

    Talal A. Al-Kassar, Dr.

    2014-10-01

    The research also demonstrates the need to include measures of both financial and non-financial performance in the evaluation as they complement each other. Without both financial and non-financial, the evaluation process is incomplete and does not provide desired results or the correct image of the process. The research suggests including comprehensive measures of performance evaluation of projects by using indicators of adopted criteria. Thus, the application of both models leads to better results and assists users in maintaining greater objectivity while obtaining more accurate results than from analysis based on personal evaluation alone.

  5. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    Science.gov (United States)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  6. Doomed reservoirs in Kansas, USA? Climate change and groundwater mining on the Great Plains lead to unsustainable surface water storage

    Science.gov (United States)

    Brikowski, T. H.

    2008-06-01

    SummaryStreamflow declines on the Great Plains of the US are causing many Federal reservoirs to become profoundly inefficient, and will eventually drive them into unsustainability as negative annual reservoir water budgets become more common. The streamflow declines are historically related to groundwater mining, but since the mid-1980s correlate increasingly with climate. This study highlights that progression toward unsustainability, and shows that future climate change will continue streamflow declines at historical rates, with severe consequences for surface water supply. An object lesson is Optima Lake in the Oklahoma Panhandle, where streamflows have declined 99% since the 1960s and the reservoir has never been more than 5% full. Water balances for the four westernmost Federal reservoirs in Kansas (Cedar Bluff, Keith Sebelius, Webster and Kirwin) show similar tendencies. For these four, reservoir inflow has declined by 92%, 73%, 81% and 64% respectively since the 1950s. Since 1990 total evaporated volumes relative to total inflows amounted to 68%, 83%, 24% and 44% respectively. Predictions of streamflow and reservoir performance based on climate change models indicate 70% chance of steady decline after 2007, with a ˜50% chance of failure (releases by gravity flow impossible) of Cedar Bluff Reservoir between 2007 and 2050. Paradoxically, a 30% chance of storage increase prior 2020 is indicated, followed by steady declines through 2100. Within 95% confidence the models predict >50% decline in surface water resources between 2007 and 2050. Ultimately, surface storage of water resources may prove unsustainable in this region, forcing conversion to subsurface storage.

  7. Translation Ambiguity but Not Word Class Predicts Translation Performance

    Science.gov (United States)

    Prior, Anat; Kroll, Judith F.; Macwhinney, Brian

    2013-01-01

    We investigated the influence of word class and translation ambiguity on cross-linguistic representation and processing. Bilingual speakers of English and Spanish performed translation production and translation recognition tasks on nouns and verbs in both languages. Words either had a single translation or more than one translation. Translation…

  8. Predictive Performance Tuning of OpenACC Accelerated Applications

    KAUST Repository

    Siddiqui, Shahzeb; Feki, Saber

    2014-01-01

    , with the introduction of high level programming models such as OpenACC [1] and OpenMP 4.0 [2], these devices are becoming more accessible and practical to use by a larger scientific community. However, performance optimization of OpenACC accelerated applications usually

  9. Predicting Performance Under Acute Stress : The Role of Individual Characteristics

    NARCIS (Netherlands)

    Delahaij, R.; Dam, K. van; Gaillard, A.W.K.; Soeters, J.

    2011-01-01

    This prospective study examined how differences in coping style, coping self-efficacy, and metacognitive awareness influence coping behavior and performance during a realistic acute stressful exercise in 2 military samples (n = 122 and n = 132). Results showed that coping self-efficacy and coping

  10. Goal orientations predict academic performance beyond intelligence and personality

    NARCIS (Netherlands)

    Steinmayr, R.; Bipp, T.; Spinath, B.

    2011-01-01

    Goal orientations are thought to be an important predictor of scholastic achievement. The present paper investigated the joint influence of goal orientations, intelligence, and personality on school performance in a sample of N = 520 11th and 12th graders (303 female; mean age M = 16.94 years).

  11. Fine-motor skills testing and prediction of endovascular performance

    DEFF Research Database (Denmark)

    Bech, Bo; Lönn, Lars; Schroeder, Torben V

    2013-01-01

    Performing endovascular procedures requires good control of fine-motor digital movements and hand-eye coordination. Objective assessment of such skills is difficult. Trainees acquire control of catheter/wire movements at various paces. However, little is known to what extent talent plays for novice...

  12. Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

    Science.gov (United States)

    Ye, Qiang

    2010-01-01

    Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

  13. Predicting timing performance of advanced mechatronics control systems

    NARCIS (Netherlands)

    Voeten, J.P.M.; Hendriks, T.; Theelen, B.D.; Schuddemat, J.; Tabingh Suermondt, W.; Gemei, J.; Kotterink, C.; Huet, van J.; Eichler, G.; Kuepper, A.; Schau, V.; Fouchal, H.; Unger, H.

    2011-01-01

    Embedded control is a key product technology differentiator for many high-tech industries, including ASML. The strong increase in complexity of embedded control systems, combined with the occurrence of late changes in control requirements, results in many timing performance problems showing up only

  14. Students' Metacomprehension Knowledge: Components That Predict Comprehension Performance

    Science.gov (United States)

    Zabrucky, Karen M.; Moore, DeWayne; Agler, Lin-Miao Lin; Cummings, Andrea M.

    2015-01-01

    In the present study, we assessed students' metacomprehension knowledge and examined the components of knowledge most related to comprehension of expository texts. We used the Revised Metacomprehension Scale (RMCS) to investigate the relations between students' metacomprehension knowledge and comprehension performance. Students who evaluated and…

  15. Adult age differences in predicting memory performance: the effects of normative information and task experience.

    Science.gov (United States)

    McDonald-Miszczak, L; Hunter, M A; Hultsch, D F

    1994-03-01

    Two experiments addressed the effects of task information and experience on younger and older adults' ability to predict their memory for words. The first study examined the effects of normative task information on subjects' predictions for 30-word lists across three trials. The second study looked at the effects of making predictions and recalling either an easy (15) or a difficult (45) word list prior to making predictions and recalling a moderately difficult (30) word list. The results from both studies showed that task information and experience affected subjects' predictions and that elderly adults predicted their performance more accurately than younger adults.

  16. Mean platelet volume (MPV) predicts middle distance running performance.

    Science.gov (United States)

    Lippi, Giuseppe; Salvagno, Gian Luca; Danese, Elisa; Skafidas, Spyros; Tarperi, Cantor; Guidi, Gian Cesare; Schena, Federico

    2014-01-01

    Running economy and performance in middle distance running depend on several physiological factors, which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is available about hematological predictors of middle distance running time, we investigated whether some hematological parameters may be associated with middle distance running performance in a large sample of recreational runners. The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years), who successfully concluded a 21.1 km half-marathon at 75-85% of their maximal aerobic power (VO2max). Whole blood was collected 10 min before the run started and immediately thereafter, and hematological testing was completed within 2 hours after sample collection. The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas those of mean corpuscular volume (MCV), platelets, mean platelet volume (MPV), white blood cells (WBCs), neutrophils and monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH), red blood cell distribution width (RDW), MPV, reticulocyte hemoglobin concentration (RetCHR), and post-run values of MCH, RDW, MPV, monocytes and RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate, body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running performance in univariate analysis were entered as independent variables, only MPV values before and after the trial remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run (p = 0.042), but not thereafter (p = 0.247), remained significantly associated with running

  17. Mean platelet volume (MPV predicts middle distance running performance.

    Directory of Open Access Journals (Sweden)

    Giuseppe Lippi

    Full Text Available Running economy and performance in middle distance running depend on several physiological factors, which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is available about hematological predictors of middle distance running time, we investigated whether some hematological parameters may be associated with middle distance running performance in a large sample of recreational runners.The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years, who successfully concluded a 21.1 km half-marathon at 75-85% of their maximal aerobic power (VO2max. Whole blood was collected 10 min before the run started and immediately thereafter, and hematological testing was completed within 2 hours after sample collection.The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas those of mean corpuscular volume (MCV, platelets, mean platelet volume (MPV, white blood cells (WBCs, neutrophils and monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH, red blood cell distribution width (RDW, MPV, reticulocyte hemoglobin concentration (RetCHR, and post-run values of MCH, RDW, MPV, monocytes and RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate, body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running performance in univariate analysis were entered as independent variables, only MPV values before and after the trial remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run (p = 0.042, but not thereafter (p = 0.247, remained significantly associated with running

  18. Prediction of shale prospectivity from seismically-derived reservoir and completion qualities: Application to a shale-gas field, Horn River Basin, Canada

    Science.gov (United States)

    Mo, Cheol Hoon; Lee, Gwang H.; Jeoung, Taek Ju; Ko, Kyung Nam; Kim, Ki Soo; Park, Kyung-sick; Shin, Chang Hoon

    2018-04-01

    Prospective shale plays require a combination of good reservoir and completion qualities. Total organic carbon (TOC) is an important reservoir quality and brittleness is the most critical condition for completion quality. We analyzed seismically-derived brittleness and TOC to investigate the prospectivity of the Horn River Group shale (the Muskwa, Otter Park, Evie shales) of a shale-gas field in the western Horn River Basin, British Columbia, Canada. We used the λρ-μρ brittleness template, constructed from the mineralogy-based brittleness index (MBI) and elastic logs from two wells, to convert the λρ and μρ volumes from prestack seismic inversion to the volume for the brittleness petrotypes (most brittle, intermediate, and least brittle). The probability maps of the most brittle petrotype for the three shales were generated from Bayesian classification, based on the λρ-μρ template. The relationship between TOC and P-wave and S-wave velocity ratio (VP/VS) at the wells allowed the conversion of the VP/VS volume from prestack inversion to the TOC volume, which in turn was used to construct the TOC maps for the three shales. Increased TOC is correlated with high brittleness, contrasting with the commonly-held understanding. Therefore, the prospectivity of the shales in the study area can be represented by high brittleness and increased TOC. We propose a shale prospectivity index (SPI), computed by the arithmetic average of the normalized probability of the most brittle petrotype and the normalized TOC. The higher SPI corresponds to higher production rates in the Muskwa and Evie shales. The areas of the highest SPI have not been fully tested. The future drilling should be focused on these areas to increase the economic viability of the field.

  19. Evaluation of field development plans using 3-D reservoir modelling

    Energy Technology Data Exchange (ETDEWEB)

    Seifert, D.; Lewis, J.J.M. [Heriot-Watt Univ., Edinburgh (United Kingdom); Newbery, J.D.H. [Conoco, UK Ltd., Aberdeen (United Kingdom)] [and others

    1997-08-01

    Three-dimensional reservoir modelling has become an accepted tool in reservoir description and is used for various purposes, such as reservoir performance prediction or integration and visualisation of data. In this case study, a small Northern North Sea turbiditic reservoir was to be developed with a line drive strategy utilising a series of horizontal producer and injector pairs, oriented north-south. This development plan was to be evaluated and the expected outcome of the wells was to be assessed and risked. Detailed analyses of core, well log and analogue data has led to the development of two geological {open_quotes}end member{close_quotes} scenarios. Both scenarios have been stochastically modelled using the Sequential Indicator Simulation method. The resulting equiprobable realisations have been subjected to detailed statistical well placement optimisation techniques. Based upon bivariate statistical evaluation of more than 1000 numerical well trajectories for each of the two scenarios, it was found that the wells inclinations and lengths had a great impact on the wells success, whereas the azimuth was found to have only a minor impact. After integration of the above results, the actual well paths were redesigned to meet external drilling constraints, resulting in substantial reductions in drilling time and costs.

  20. Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

    Science.gov (United States)

    Hung, Andrew J; Chen, Jian; Che, Zhengping; Nilanon, Tanachat; Jarc, Anthony; Titus, Micha; Oh, Paul J; Gill, Inderbir S; Liu, Yan

    2018-05-01

    Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting. The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p algorithm in predicting, were largely related to camera manipulation. To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

  1. A Bayesian Performance Prediction Model for Mathematics Education: A Prototypical Approach for Effective Group Composition

    Science.gov (United States)

    Bekele, Rahel; McPherson, Maggie

    2011-01-01

    This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…

  2. Evaluation of an Empirical Reservoir Shape Function to Define Sediment Distributions in Small Reservoirs

    Directory of Open Access Journals (Sweden)

    Bogusław Michalec

    2015-08-01

    Full Text Available Understanding and defining the spatial distribution of sediment deposited in reservoirs is essential not only at the design stage but also during the operation. The majority of research concerns the distribution of sediment deposition in medium and large water reservoirs. Most empirical methods do not provide satisfactory results when applied to the determination of sediment deposition in small reservoirs. Small reservoir’s volumes do not exceed 5 × 106 m3 and their capacity-inflow ratio is less than 10%. Long-term silting measurements of three small reservoirs were used to evaluate the method described by Rahmanian and Banihashemi for predicting sediment distributions in small reservoirs. Rahmanian and Banihashemi stated that their model of distribution of sediment deposition in water reservoir works well for a long duration operation. In the presented study, the silting rate was used in order to determine the long duration operation. Silting rate is a quotient of volume of the sediment deposited in the reservoir and its original volume. It was stated that when the silting rate had reached 50%, the sediment deposition in the reservoir may be described by an empirical reservoir depth shape function (RDSF.

  3. Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft

    Science.gov (United States)

    Birckelbaw, Lourdes G.

    1992-01-01

    A ski jump model was developed to predict ski jump takeoff performance for a short takeoff and vertical landing (STOVL) aircraft. The objective was to verify the model with results from a piloted simulation of a mixed flow, remote lift STOVL aircraft. The prediction model is discussed. The predicted results are compared with the piloted simulation results. The ski jump model can be utilized for basic research of other thrust vectoring STOVL aircraft performing a ski jump takeoff.

  4. Evaluation and prediction of the performance of positive displacement motor

    Energy Technology Data Exchange (ETDEWEB)

    Tudor, R.; Ginzburg, L. [Canadian Fracmaster Ltd., Calgary, AB (Canada); Xu, H. [Japan National Oil Corp (Japan); Li, J.; Robello, G.; Grigor, C.

    1998-12-31

    Test results of positive displacement motors (PDMs) collected by using various PDMs from a number of different suppliers have been analyzed. Various correlations have been developed and motor performance pumped with incompressible drilling fluid was evaluated based on test data provided by suppliers in the form of pressure drop versus torque output. Conclusions drawn from the study suggest that when a motor is operated at less than full load, the correlation between mechanical power and hydraulic power across the PDM power section can be described with a simple linear equation (different for each PDM type). Assuming the availability of patented geometric information for each PDM type, the performance of PDMs can be described by both the geometric parameters of the motor and the rheological properties of the circulation fluid. 9 refs., 8 figs.

  5. Reservoir Models for Gas Hydrate Numerical Simulation

    Science.gov (United States)

    Boswell, R.

    2016-12-01

    Scientific and industrial drilling programs have now providing detailed information on gas hydrate systems that will increasingly be the subject of field experiments. The need to carefully plan these programs requires reliable prediction of reservoir response to hydrate dissociation. Currently, a major emphasis in gas hydrate modeling is the integration of thermodynamic/hydrologic phenomena with geomechanical response for both reservoir and bounding strata. However, also critical to the ultimate success of these efforts is the appropriate development of input geologic models, including several emerging issues, including (1) reservoir heterogeneity, (2) understanding of the initial petrophysical characteristics of the system (reservoirs and seals), the dynamic evolution of those characteristics during active dissociation, and the interdependency of petrophysical parameters and (3) the nature of reservoir boundaries. Heterogeneity is ubiquitous aspect of every natural reservoir, and appropriate characterization is vital. However, heterogeneity is not random. Vertical variation can be evaluated with core and well log data; however, core data often are challenged by incomplete recovery. Well logs also provide interpretation challenges, particularly where reservoirs are thinly-bedded due to limitation in vertical resolution. This imprecision will extend to any petrophysical measurements that are derived from evaluation of log data. Extrapolation of log data laterally is also complex, and should be supported by geologic mapping. Key petrophysical parameters include porosity, permeability and it many aspects, and water saturation. Field data collected to date suggest that the degree of hydrate saturation is strongly controlled by/dependant upon reservoir quality and that the ratio of free to bound water in the remaining pore space is likely also controlled by reservoir quality. Further, those parameters will also evolve during dissociation, and not necessary in a simple

  6. Revised MITG design, fabrication procedure, and performance predictions

    International Nuclear Information System (INIS)

    Schock, A.

    1983-01-01

    The design, analysis, and key features of the Modular Isotopic Thermoelectric Generator (MITG) were described in a 1981 IECEC paper; and the design, fabrication, testing, and post-test analysis of test assemblies simulating prototypical MITG modules were described in preceding papers in these proceedings. These analyses succeeded in identifying and explaining the principal causes of thermal-stress problems encountered in the tests, and in confirming the effectiveness of design changes for alleviating them. The present paper presents additional design improvements for solving these and other problems, and describes new thermoelectric material properties generated by independent laboratories over the past two years. Based on these changes and on a revised fabrication procedure, it presents a reoptimization of the MITG design and computes the power-to-weight ratio for the revised design. That ratio is appreciably lower than the 1981 prediction, primarily because of changes in material properties; but it is still much higher than the specific power of current-generation RTGs

  7. Research of performance prediction to energy on hydraulic turbine

    International Nuclear Information System (INIS)

    Quan, H; Li, R N; Li, Q F; Han, W; Su, Q M

    2012-01-01

    Refer to the low specific speed Francis turbine blade design principle and double-suction pump structure. Then, design a horizontal double-channel hydraulic turbine Francis. Through adding different guide vane airfoil and and no guide vane airfoil on the hydraulic conductivity components to predict hydraulic turbine energy and using Fluent software to numerical simulation that the operating conditions and point. The results show that the blade pressure surface and suction surface pressure is low when the hydraulic turbine installation is added standard positive curvature of the guide vane and modified positive curvature of guide vane. Therefore, the efficiency of energy recovery is low. However, the pressure of negative curvature guide vane and symmetric guide vane added on hydraulic turbine installations is larger than that of the former ones, and it is conducive to working of runner. With the decreasing of guide vane opening, increasing of inlet angle, flow state gets significantly worse. Then, others obvious phenomena are that the reflux and horizontal flow appeared in blade pressure surface. At the same time, the vortex was formed in Leaf Road, leading to the loss of energy. Through analyzing the distribution of pressure, velocity, flow lines of over-current flow in the the back hydraulic conductivity components in above programs we can known that the hydraulic turbine installation added guide vane is more reasonable than without guide vanes, it is conducive to improve efficiency of energy conversion.

  8. Integration of advanced geoscience and engineering techniques to quantify interwell heterogeneity in reservoir models. Final report, September 29, 1993--September 30, 1996

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, W.W.; Buckley, J.S.; Ouenes, A.

    1997-05-01

    The goal of this three-year project was to provide a quantitative definition of reservoir heterogeneity. This objective was accomplished through the integration of geologic, geophysical, and engineering databases into a multi-disciplinary understanding of reservoir architecture and associated fluid-rock and fluid-fluid interactions. This interdisciplinary effort integrated geological and geophysical data with engineering and petrophysical results through reservoir simulation to quantify reservoir architecture and the dynamics of fluid-rock and fluid-fluid interactions. An improved reservoir description allows greater accuracy and confidence during simulation and modeling as steps toward gaining greater recovery efficiency from existing reservoirs. A field laboratory, the Sulimar Queen Unit, was available for the field research. Several members of the PRRC staff participated in the development of improved reservoir description by integration of the field and laboratory data as well as in the development of quantitative reservoir models to aid performance predictions. Subcontractors from Stanford University and the University of Texas at Austin (UT) collaborated in the research and participated in the design and interpretation of field tests. The three-year project was initiated in September 1993 and led to the development and application of various reservoir description methodologies. A new approach for visualizing production data graphically was developed and implemented on the Internet. Using production data and old gamma rays logs, a black oil reservoir model that honors both primary and secondary performance was developed. The old gamma ray logs were used after applying a resealing technique, which was crucial for the success of the project. In addition to the gamma ray logs, the development of the reservoir model benefitted from an inverse Drill Stem Test (DST) technique which provided initial estimates of the reservoir permeability at different wells.

  9. Performance predictions affect attentional processes of event-based prospective memory.

    Science.gov (United States)

    Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

    2013-09-01

    To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Investigating the effects of rock porosity and permeability on the performance of nitrogen injection into a southern Iranian oil reservoirs through neural network

    Science.gov (United States)

    Gheshmi, M. S.; Fatahiyan, S. M.; Khanesary, N. T.; Sia, C. W.; Momeni, M. S.

    2018-03-01

    In this work, a comprehensive model for Nitrogen injection into an oil reservoir (southern Iranian oil fields) was developed and used to investigate the effects of rock porosity and permeability on the oil production rate and the reservoir pressure decline. The model was simulated and developed by using ECLIPSE300 software, which involved two scenarios as porosity change and permeability changes in the horizontal direction. We found that the maximum pressure loss occurs at a porosity value of 0.07, which later on, goes to pressure buildup due to reservoir saturation with the gas. Also we found that minimum pressure loss is encountered at porosity 0.46. Increases in both pressure and permeability in the horizontal direction result in corresponding increase in the production rate, and the pressure drop speeds up at the beginning of production as it increases. However, afterwards, this pressure drop results in an increase in pressure because of reservoir saturation. Besides, we determined the regression values, R, for the correlation between pressure and total production, as well as for the correlation between permeability and the total production, using neural network discipline.

  11. Cognition and procedure representational requirements for predictive human performance models

    Science.gov (United States)

    Corker, K.

    1992-01-01

    Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods

  12. Algorithms and Methods for High-Performance Model Predictive Control

    DEFF Research Database (Denmark)

    Frison, Gianluca

    routines employed in the numerical tests. The main focus of this thesis is on linear MPC problems. In this thesis, both the algorithms and their implementation are equally important. About the implementation, a novel implementation strategy for the dense linear algebra routines in embedded optimization...... is proposed, aiming at improving the computational performance in case of small matrices. About the algorithms, they are built on top of the proposed linear algebra, and they are tailored to exploit the high-level structure of the MPC problems, with special care on reducing the computational complexity....

  13. Basic considerations in predicting error probabilities in human task performance

    International Nuclear Information System (INIS)

    Fleishman, E.A.; Buffardi, L.C.; Allen, J.A.; Gaskins, R.C. III

    1990-04-01

    It is well established that human error plays a major role in the malfunctioning of complex systems. This report takes a broad look at the study of human error and addresses the conceptual, methodological, and measurement issues involved in defining and describing errors in complex systems. In addition, a review of existing sources of human reliability data and approaches to human performance data base development is presented. Alternative task taxonomies, which are promising for establishing the comparability on nuclear and non-nuclear tasks, are also identified. Based on such taxonomic schemes, various data base prototypes for generalizing human error rates across settings are proposed. 60 refs., 3 figs., 7 tabs

  14. Area of Interest 1, CO2 at the Interface. Nature and Dynamics of the Reservoir/Caprock Contact and Implications for Carbon Storage Performance

    Energy Technology Data Exchange (ETDEWEB)

    Mozley, Peter [New Mexico Institute Of Mining And Technology, Socorro, NM (United States); Evans, James [New Mexico Institute Of Mining And Technology, Socorro, NM (United States); Dewers, Thomas [New Mexico Institute Of Mining And Technology, Socorro, NM (United States)

    2014-10-31

    We examined the influence of geologic features present at the reservoir/caprock interface on the transmission of supercritical CO2 into and through caprock. We focused on the case of deformation-band faults in reservoir lithologies that intersect the interface and transition to opening-mode fractures in caprock lithologies. Deformation-band faults are exceeding common in potential CO2 injection units and our fieldwork in Utah indicates that this sort of transition is common. To quantify the impact of these interface features on flow and transport we first described the sedimentology and permeability characteristics of selected sites along the Navajo Sandstone (reservoir lithology) and Carmel Formation (caprock lithology) interface, and along the Slickrock Member (reservoir lithology) and Earthy Member (caprock lithology) of the Entrada Sandstone interface, and used this information to construct conceptual permeability models for numerical analysis. We then examined the impact of these structures on flow using single-phase and multiphase numerical flow models for these study sites. Key findings include: (1) Deformation-band faults strongly compartmentalize the reservoir and largely block cross-fault flow of supercritical CO2. (2) Significant flow of CO2 through the fractures is possible, however, the magnitude is dependent on the small-scale geometry of the contact between the opening-mode fracture and the deformation band fault. (3) Due to the presence of permeable units in the caprock, caprock units are capable of storing significant volumes of CO2, particularly when the fracture network does not extend all the way through the caprock. The large-scale distribution of these deformation-bandfault-to-opening-mode-fractures is related to the curvature of the beds, with greater densities of fractures in high curvature regions. We also examined core and outcrops from the Mount Simon Sandstone and Eau Claire

  15. Can Medical School Performance Predict Residency Performance? Resident Selection and Predictors of Successful Performance in Obstetrics and Gynecology

    Science.gov (United States)

    Stohl, Hindi E.; Hueppchen, Nancy A.; Bienstock, Jessica L.

    2010-01-01

    Background During the evaluation process, Residency Admissions Committees typically gather data on objective and subjective measures of a medical student's performance through the Electronic Residency Application Service, including medical school grades, standardized test scores, research achievements, nonacademic accomplishments, letters of recommendation, the dean's letter, and personal statements. Using these data to identify which medical students are likely to become successful residents in an academic residency program in obstetrics and gynecology is difficult and to date, not well studied. Objective To determine whether objective information in medical students' applications can help predict resident success. Method We performed a retrospective cohort study of all residents who matched into the Johns Hopkins University residency program in obstetrics and gynecology between 1994 and 2004 and entered the program through the National Resident Matching Program as a postgraduate year-1 resident. Residents were independently evaluated by faculty and ranked in 4 groups according to perceived level of success. Applications from residents in the highest and lowest group were abstracted. Groups were compared using the Fisher exact test and the Student t test. Results Seventy-five residents met inclusion criteria and 29 residents were ranked in the highest and lowest quartiles (15 in highest, 14 in lowest). Univariate analysis identified no variables as consistent predictors of resident success. Conclusion In a program designed to train academic obstetrician-gynecologists, objective data from medical students' applications did not correlate with successful resident performance in our obstetrics-gynecology residency program. We need to continue our search for evaluation criteria that can accurately and reliably select the medical students that are best fit for our specialty. PMID:21976076

  16. Data assimilation method for fractured reservoirs using mimetic finite differences and ensemble Kalman filter

    KAUST Repository

    Ping, Jing

    2017-05-19

    Optimal management of subsurface processes requires the characterization of the uncertainty in reservoir description and reservoir performance prediction. For fractured reservoirs, the location and orientation of fractures are crucial for predicting production characteristics. With the help of accurate and comprehensive knowledge of fracture distributions, early water/CO 2 breakthrough can be prevented and sweep efficiency can be improved. However, since the rock property fields are highly non-Gaussian in this case, it is a challenge to estimate fracture distributions by conventional history matching approaches. In this work, a method that combines vector-based level-set parameterization technique and ensemble Kalman filter (EnKF) for estimating fracture distributions is presented. Performing the necessary forward modeling is particularly challenging. In addition to the large number of forward models needed, each model is used for sampling of randomly located fractures. Conventional mesh generation for such systems would be time consuming if possible at all. For these reasons, we rely on a novel polyhedral mesh method using the mimetic finite difference (MFD) method. A discrete fracture model is adopted that maintains the full geometry of the fracture network. By using a cut-cell paradigm, a computational mesh for the matrix can be generated quickly and reliably. In this research, we apply this workflow on 2D two-phase fractured reservoirs. The combination of MFD approach, level-set parameterization, and EnKF provides an effective solution to address the challenges in the history matching problem of highly non-Gaussian fractured reservoirs.

  17. Submillimetre wave imaging and security: imaging performance and prediction

    Science.gov (United States)

    Appleby, R.; Ferguson, S.

    2016-10-01

    Within the European Commission Seventh Framework Programme (FP7), CONSORTIS (Concealed Object Stand-Off Real-Time Imaging for Security) has designed and is fabricating a stand-off system operating at sub-millimetre wave frequencies for the detection of objects concealed on people. This system scans people as they walk by the sensor. This paper presents the top level system design which brings together both passive and active sensors to provide good performance. The passive system operates in two bands between 100 and 600GHz and is based on a cryogen free cooled focal plane array sensor whilst the active system is a solid-state 340GHz radar. A modified version of OpenFX was used for modelling the passive system. This model was recently modified to include realistic location-specific skin temperature and to accept animated characters wearing up to three layers of clothing that move dynamically, such as those typically found in cinematography. Targets under clothing have been modelled and the performance simulated. The strengths and weaknesses of this modelling approach are discussed.

  18. Investigation into the performance of different models for predicting stutter.

    Science.gov (United States)

    Bright, Jo-Anne; Curran, James M; Buckleton, John S

    2013-07-01

    In this paper we have examined five possible models for the behaviour of the stutter ratio, SR. These were two log-normal models, two gamma models, and a two-component normal mixture model. A two-component normal mixture model was chosen with different behaviours of variance; at each locus SR was described with two distributions, both with the same mean. The distributions have difference variances: one for the majority of the observations and a second for the less well-behaved ones. We apply each model to a set of known single source Identifiler™, NGM SElect™ and PowerPlex(®) 21 DNA profiles to show the applicability of our findings to different data sets. SR determined from the single source profiles were compared to the calculated SR after application of the models. The model performance was tested by calculating the log-likelihoods and comparing the difference in Akaike information criterion (AIC). The two-component normal mixture model systematically outperformed all others, despite the increase in the number of parameters. This model, as well as performing well statistically, has intuitive appeal for forensic biologists and could be implemented in an expert system with a continuous method for DNA interpretation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  19. Predicting performance in competitive apnea diving, part II: dynamic apnoea.

    Science.gov (United States)

    Schagatay, Erika

    2010-03-01

    Part I of this series of articles identified the main physiological factors defining the limits of static apnea, while this paper reviews the factors involved when physical work is added in the dynamic distance disciplines, performed in shallow water in a swimming pool. Little scientific work has been done concerning the prerequisites and limitations of swimming with or without fins whilst breath holding to extreme limits. Apneic duration influences all competitive apnea disciplines, and can be prolonged by any means that increase gas storage or tolerance to asphyxia, or reduce metabolic rate, as reviewed in the first article. For horizontal underwater distance swimming, the main challenge is to restrict metabolism despite the work, and to direct blood flow only to areas where demand is greatest, to allow sustained function. Here, work economy, local tissue energy and oxygen stores and the anaerobic capacity of the muscles are key components. Improvements in swimming techniques and, especially in swimming with fins, equipment have already contributed to enhanced performance and may do so further. High lactate levels observed after competition swims suggest a high anaerobic component, and muscle hypoxia could ultimately limit muscle work and swimming distance. However, the frequency of syncope, especially in swimming without fins, suggests that cerebral oxygenation may often be compromised before this occurs. In these pool disciplines, safety is high and the dive can be interrupted by the competitor or safety diver within seconds. The safety routines in place during pool competitions are described.

  20. SEISMIC ATTENUATION FOR RESERVOIR CHARACTERIZATION

    Energy Technology Data Exchange (ETDEWEB)

    Joel Walls; M.T. Taner; Naum Derzhi; Gary Mavko; Jack Dvorkin

    2003-12-01

    We have developed and tested technology for a new type of direct hydrocarbon detection. The method uses inelastic rock properties to greatly enhance the sensitivity of surface seismic methods to the presence of oil and gas saturation. These methods include use of energy absorption, dispersion, and attenuation (Q) along with traditional seismic attributes like velocity, impedance, and AVO. Our approach is to combine three elements: (1) a synthesis of the latest rock physics understanding of how rock inelasticity is related to rock type, pore fluid types, and pore microstructure, (2) synthetic seismic modeling that will help identify the relative contributions of scattering and intrinsic inelasticity to apparent Q attributes, and (3) robust algorithms that extract relative wave attenuation attributes from seismic data. This project provides: (1) Additional petrophysical insight from acquired data; (2) Increased understanding of rock and fluid properties; (3) New techniques to measure reservoir properties that are not currently available; and (4) Provide tools to more accurately describe the reservoir and predict oil location and volumes. These methodologies will improve the industry's ability to predict and quantify oil and gas saturation distribution, and to apply this information through geologic models to enhance reservoir simulation. We have applied for two separate patents relating to work that was completed as part of this project.

  1. Predicting Performance: A Comparison of University Supervisors' Predictions and Teacher Candidates' Scores on a Teaching Performance Assessment

    Science.gov (United States)

    Sandholtz, Judith Haymore; Shea, Lauren M.

    2012-01-01

    The implementation of teaching performance assessments has prompted a range of concerns. Some educators question whether these assessments provide information beyond what university supervisors gain through their formative evaluations and classroom observations of candidates. This research examines the relationship between supervisors' predictions…

  2. Towards an Improved Represenation of Reservoirs and Water Management in a Land Surface-Hydrology Model

    Science.gov (United States)

    Yassin, F.; Anis, M. R.; Razavi, S.; Wheater, H. S.

    2017-12-01

    Water management through reservoirs, diversions, and irrigation have significantly changed river flow regimes and basin-wide energy and water balance cycles. Failure to represent these effects limits the performance of land surface-hydrology models not only for streamflow prediction but also for the estimation of soil moisture, evapotranspiration, and feedbacks to the atmosphere. Despite recent research to improve the representation of water management in land surface models, there remains a need to develop improved modeling approaches that work in complex and highly regulated basins such as the 406,000 km2 Saskatchewan River Basin (SaskRB). A particular challenge for regional and global application is a lack of local information on reservoir operational management. To this end, we implemented a reservoir operation, water abstraction, and irrigation algorithm in the MESH land surface-hydrology model and tested it over the SaskRB. MESH is Environment Canada's Land Surface-hydrology modeling system that couples Canadian Land Surface Scheme (CLASS) with hydrological routing model. The implemented reservoir algorithm uses an inflow-outflow relationship that accounts for the physical characteristics of reservoirs (e.g., storage-area-elevation relationships) and includes simplified operational characteristics based on local information (e.g., monthly target volume and release under limited, normal, and flood storage zone). The irrigation algorithm uses the difference between actual and potential evapotranspiration to estimate irrigation water demand. This irrigation demand is supplied from the neighboring reservoirs/diversion in the river system. We calibrated the model enabled with the new reservoir and irrigation modules in a multi-objective optimization setting. Results showed that the reservoir and irrigation modules significantly improved the MESH model performance in generating streamflow and evapotranspiration across the SaskRB and that this our approach provides

  3. Plasma property and performance prediction for mercury ion thrusters

    Science.gov (United States)

    Longhurst, G. R.; Wilbur, P. J.

    1979-01-01

    The discharge chambers of mercury ion thrusters are modelled so the principal effects and processes which govern discharge plasma properties and thruster performance are described. The conservation relations for mass, charge and energy when applied to the Maxwellian electron population in the ion production region yield equations which may be made one-dimensional by the proper choice of coordinates. Solutions to these equations with the appropriate boundary conditions give electron density and temperature profiles which agree reasonably well with measurements. It is then possible to estimate plasma properties from thruster design data and those operating parameters which are directly controllable. By varying the operating parameter inputs to the computer code written to solve these equations, perfromance curves are obtained which agree quite well with measurements.

  4. Predicting neuropsychological test performance on the basis of temporal orientation.

    Science.gov (United States)

    Ryan, Joseph J; Glass, Laura A; Bartels, Jared M; Bergner, CariAnn M; Paolo, Anthony M

    2009-05-01

    Temporal orientation is often disrupted in the context of psychiatric or neurological disease; tests assessing this function are included in most mental status examinations. The present study examined the relationship between scores on the Temporal Orientation Scale (TOS) and performance on a battery of tests that assess memory, language, and cognitive functioning in a sample of patients with Alzheimer's disease (N = 55). Pearson-product moment correlations showed that, in all but two instances, the TOS was significantly correlated with each neuropsychological measure, p values < or = .05. Also, severely disoriented (i.e., TOS score < or = -8) patients were consistently 'impaired' on memory tests but not on tests of language and general cognitive functioning.

  5. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    International Nuclear Information System (INIS)

    Shibata, H.; Watanabe, Y.; Suzuki, K.

    2016-01-01

    In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

  6. Prediction of the Effect of Vortex Generators on Airfoil Performance

    International Nuclear Information System (INIS)

    Sørensen, Niels N; Zahle, F; Bak, C; Vronsky, T

    2014-01-01

    Vortex Generators (VGs) are widely used by the wind turbine industry, to control the flow over blade sections. The present work describes a computational fluid dynamic procedure that can handle a geometrical resolved VG on an airfoil section. After describing the method, it is applied to two different airfoils at a Reynolds number of 3 million, the FFA- W3-301 and FFA-W3-360, respectively. The computations are compared with wind tunnel measurements from the Stuttgart Laminar Wind Tunnel with respect to lift and drag variation as function of angle of attack. Even though the method does not exactly capture the measured performance, it can be used to compare different VG setups qualitatively with respect to chord- wise position, inter and intra-spacing and inclination of the VGs already in the design phase

  7. Serum 25-hydroxyvitamin D predicts cognitive performance in adults

    Directory of Open Access Journals (Sweden)

    Darwish H

    2015-08-01

    Full Text Available Hala Darwish,1 Pia Zeinoun,2 Husam Ghusn,3,4 Brigitte Khoury,2 Hani Tamim,5 Samia J Khoury6 1Hariri School of Nursing, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 2Psychiatry Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 3Internal Medicine Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 4Geriatrics Department, Ain Wazein Hospital, El Chouf, Lebanon; 5Clinical Research Institute, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 6Neurology Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon Background: Vitamin D is an endogenous hormone known to regulate calcium levels in the body and plays a role in cognitive performance. Studies have shown an association between vitamin D deficiency and cognitive impairment in older adults. Lebanon has a high 25-hydroxyvitamin D (25(OHD deficiency prevalence across all age groups. Methods: In this cross-sectional study, we explored the cognitive performance and serum 25(OHD levels using an electrochemoluminescent immunoassay in 254 older (>60 years as well as younger (30–60 years adults. Subjects’ characteristics, including age, years of education, wearing of veil, alcohol consumption, smoking, and physical exercise, were collected. Participants were screened for depression prior to cognitive screening using the Montreal Cognitive Assessment Arabic version. Visuospatial memory was tested using the Rey Complex Figure Test and Recognition Trial, and speed of processing was assessed using the Symbol Digit Modalities test. Results: Pearson’s correlation and stepwise linear regression analyses showed that a low vitamin D level was associated with greater risk of cognitive impairment in older as well as younger adults. Conclusion: These findings suggest that correction of vitamin D needs to be explored as an intervention to prevent cognitive impairment. Prospective

  8. Performance prediction for a magnetostrictive actuator using a simplified model

    Science.gov (United States)

    Yoo, Jin-Hyeong; Jones, Nicholas J.

    2018-03-01

    Iron-Gallium alloys (Galfenol) are promising transducer materials that combine high magnetostriction, desirable mechanical properties, high permeability, and a wide operational temperature range. Most of all, the material is capable of operating under tensile stress, and is relatively resistant to shock. These materials are generally characterized using a solid, cylindrically-shaped specimen under controlled compressive stress and magnetization conditions. Because the magnetostriction strongly depends on both the applied stress and magnetization, the characterization of the material is usually conducted under controlled conditions so each parameter is varied independently of the other. However, in a real application the applied stress and magnetization will not be maintained constant during operation. Even though the controlled characterization measurement gives insight into standard material properties, usage of this data in an application, while possible, is not straight forward. This study presents an engineering modeling methodology for magnetostrictive materials based on a piezo-electric governing equation. This model suggests phenomenological, nonlinear, three-dimensional functions for strain and magnetic flux density responses as functions of applied stress and magnetic field. Load line performances as a function of maximum magnetic field input were simulated based on the model. To verify the modeling performance, a polycrystalline magnetostrictive rod (Fe-Ga alloy, Galfenol) was characterized under compressive loads using a dead-weight test setup, with strain gages on the rod and a magnetic field driving coil around the sample. The magnetic flux density through the Galfenol rod was measured with a sensing coil; the compressive loads were measured using a load cell on the bottom of the Galfenol rod. The experimental results are compared with the simulation results using the suggested model, showing good agreement.

  9. Analog readout for optical reservoir computers

    OpenAIRE

    Smerieri, Anteo; Duport, François; Paquot, Yvan; Schrauwen, Benjamin; Haelterman, Marc; Massar, Serge

    2012-01-01

    Reservoir computing is a new, powerful and flexible machine learning technique that is easily implemented in hardware. Recently, by using a time-multiplexed architecture, hardware reservoir computers have reached performance comparable to digital implementations. Operating speeds allowing for real time information operation have been reached using optoelectronic systems. At present the main performance bottleneck is the readout layer which uses slow, digital postprocessing. We have designed a...

  10. The joint effects of personality and workplace social exchange relationships in predicting task performance and citizenship performance.

    Science.gov (United States)

    Kamdar, Dishan; Van Dyne, Linn

    2007-09-01

    This field study examines the joint effects of social exchange relationships at work (leader-member exchange and team-member exchange) and employee personality (conscientiousness and agreeableness) in predicting task performance and citizenship performance. Consistent with trait activation theory, matched data on 230 employees, their coworkers, and their supervisors demonstrated interactions in which high quality social exchange relationships weakened the positive relationships between personality and performance. Results demonstrate the benefits of consonant predictions in which predictors and outcomes are matched on the basis of specific targets. We discuss theoretical and practical implications. (c) 2007 APA.

  11. AUTOMATED TECHNIQUE FOR FLOW MEASUREMENTS FROM MARIOTTE RESERVOIRS.

    Science.gov (United States)

    Constantz, Jim; Murphy, Fred

    1987-01-01

    The mariotte reservoir supplies water at a constant hydraulic pressure by self-regulation of its internal gas pressure. Automated outflow measurements from mariotte reservoirs are generally difficult because of the reservoir's self-regulation mechanism. This paper describes an automated flow meter specifically designed for use with mariotte reservoirs. The flow meter monitors changes in the mariotte reservoir's gas pressure during outflow to determine changes in the reservoir's water level. The flow measurement is performed by attaching a pressure transducer to the top of a mariotte reservoir and monitoring gas pressure changes during outflow with a programmable data logger. The advantages of the new automated flow measurement techniques include: (i) the ability to rapidly record a large range of fluxes without restricting outflow, and (ii) the ability to accurately average the pulsing flow, which commonly occurs during outflow from the mariotte reservoir.

  12. Learning to avoid spiders: fear predicts performance, not competence.

    Science.gov (United States)

    Luo, Xijia; Becker, Eni S; Rinck, Mike

    2018-01-05

    We used an immersive virtual environment to examine avoidance learning in spider-fearful participants. In 3 experiments, participants were asked to repeatedly lift one of 3 virtual boxes, under which either a toy car or a spider appeared and then approached the participant. Participants were not told that the probability of encountering a spider differed across boxes. When the difference was large (Exps. 1 and 2), spider-fearfuls learned to avoid spiders by lifting the few-spiders-box more often and the many-spiders-box less often than non-fearful controls did. However, they hardly managed to do so when the probability differences were small (Exp. 3), and they did not escape from threat more quickly (Exp. 2). In contrast to the observed performance differences, spider-fearfuls and non-fearfuls showed equal competence, that is comparable post-experimental knowledge about the probability to encounter spiders under the 3 boxes. The limitations and implications of the present study are discussed.

  13. Working memory capacity predicts conflict-task performance.

    Science.gov (United States)

    Gulbinaite, Rasa; Johnson, Addie

    2014-01-01

    The relationship between the ability to maintain task goals and working memory capacity (WMC) is firmly established, but evidence for WMC-related differences in conflict processing is mixed. We investigated whether WMC (measured using two complex-span tasks) mediates differences in adjustments of cognitive control in response to conflict. Participants performed a Simon task in which congruent and incongruent trials were equiprobable, but in which the proportion of congruency repetitions (congruent trials followed by congruent trials or incongruent trials followed by incongruent trials) and thus the need for trial-by-trial adjustments in cognitive control varied by block. The overall Simon effect did not depend on WMC capacity. However, for the low-WMC participants the Simon effect decreased as the proportion of congruency repetitions decreased, whereas for the high- and average-WMC participants it was relatively constant across conditions. Distribution analysis of the Simon effect showed more evidence for the inhibition of stimulus location in the low- than in the high-WMC participants, especially when the proportion of congruency repetitions was low. We hypothesize that low-WMC individuals exhibit more interference from task-irrelevant information due to weaker preparatory control prior to stimulus presentation and, thus, stronger reliance on reactive recruitment of cognitive control.

  14. Investigation and Prediction of RF Window Performance in APT Accelerators

    International Nuclear Information System (INIS)

    Humphries, S. Jr.

    1997-01-01

    The work described in this report was performed between November 1996 and May 1997 in support of the APT (Accelerator Production of Tritium) Program at Los Alamos National Laboratory. The goal was to write and to test computer programs for charged particle orbits in RF fields. The well-documented programs were written in portable form and compiled for standard personal computers for easy distribution to LANL researchers. They will be used in several APT applications including the following. Minimization of multipactor effects in the moderate β superconducting linac cavities under design for the APT accelerator. Investigation of suppression techniques for electron multipactoring in high-power RF feedthroughs. Modeling of the response of electron detectors for the protection of high power RF vacuum windows. In the contract period two new codes, Trak-RF and WaveSim, were completed and several critical benchmark etests were carried out. Trak-RF numerically tracks charged particle orbits in combined electrostatic, magnetostatic and electromagnetic fields. WaveSim determines frequency-domain RF field solutions and provides a key input to Trak-RF. The two-dimensional programs handle planar or cylindrical geometries. They have several unique characteristics

  15. ADVANCED TECHNIQUES FOR RESERVOIR SIMULATION AND MODELING OF NONCONVENTIONAL WELLS

    Energy Technology Data Exchange (ETDEWEB)

    Louis J. Durlofsky; Khalid Aziz

    2004-08-20

    Nonconventional wells, which include horizontal, deviated, multilateral and ''smart'' wells, offer great potential for the efficient management of oil and gas reservoirs. These wells are able to contact larger regions of the reservoir than conventional wells and can also be used to target isolated hydrocarbon accumulations. The use of nonconventional wells instrumented with downhole inflow control devices allows for even greater flexibility in production. Because nonconventional wells can be very expensive to drill, complete and instrument, it is important to be able to optimize their deployment, which requires the accurate prediction of their performance. However, predictions of nonconventional well performance are often inaccurate. This is likely due to inadequacies in some of the reservoir engineering and reservoir simulation tools used to model and optimize nonconventional well performance. A number of new issues arise in the modeling and optimization of nonconventional wells. For example, the optimal use of downhole inflow control devices has not been addressed for practical problems. In addition, the impact of geological and engineering uncertainty (e.g., valve reliability) has not been previously considered. In order to model and optimize nonconventional wells in different settings, it is essential that the tools be implemented into a general reservoir simulator. This simulator must be sufficiently general and robust and must in addition be linked to a sophisticated well model. Our research under this five year project addressed all of the key areas indicated above. The overall project was divided into three main categories: (1) advanced reservoir simulation techniques for modeling nonconventional wells; (2) improved techniques for computing well productivity (for use in reservoir engineering calculations) and for coupling the well to the simulator (which includes the accurate calculation of well index and the modeling of multiphase flow

  16. Study on the enhancement of hydrocarbon recovery by characterization of the reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Tae-Jin; Kwak, Young-Hoon; Huh, Dae-Gee [Korea Institute of Geology Mining and Materials, Taejon (KR)] (and others)

    1999-12-01

    The reservoir geochemistry is to understand the origin of these heterogeneities and distributions of the bitumens within the reservoir and to use them not only for exploration but for the development of the petroleums. Methods and principles of the reservoir geochemistry, which are applicable to the petroleum exploration and development, are reviewed in the study. In addition, a case study was carried out on the gas, condensate, water and bitumen samples in the reservoir, taken from the Haenam, Pohang areas and the Ulleung Basin offshore Korea. Mineral geothermometers were studied to estimate the thermal history in sedimentary basins and successfully applied to the Korean onshore and offshore basins. The opal silica-to-quartz transformation was investigated in the Pohang basin as a geothermometer. In Korean basins, the smectite-to-illite changes indicate that smectite and illite can act as the geothermometer to estimate the thermal history of the basins. The albitization reaction was also considered as a temperature indicator. Naturally fractured reservoir is an important source of oil and gas throughout the world. The properties of matrix and fracture are the key parameters in predicting the performances of naturally fractured reservoirs. A new laboratory equipment has been designed and constructed by pressure pulse method to determine the properties, which are (1) the porosity of matrix, (2) the permeability of matrix, (3) the effective width of the fractures, and the permeability of the fractures. (author). 97 refs.

  17. Predictive validity of pre-admission assessments on medical student performance.

    Science.gov (United States)

    Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

    2017-11-24

    To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

  18. Reservoir Engineering Management Program

    Energy Technology Data Exchange (ETDEWEB)

    Howard, J.H.; Schwarz, W.J.

    1977-12-14

    The Reservoir Engineering Management Program being conducted at Lawrence Berkeley Laboratory includes two major tasks: 1) the continuation of support to geothermal reservoir engineering related work, started under the NSF-RANN program and transferred to ERDA at the time of its formation; 2) the development and subsequent implementation of a broad plan for support of research in topics related to the exploitation of geothermal reservoirs. This plan is now known as the GREMP plan. Both the NSF-RANN legacies and GREMP are in direct support of the DOE/DGE mission in general and the goals of the Resource and Technology/Resource Exploitation and Assessment Branch in particular. These goals are to determine the magnitude and distribution of geothermal resources and reduce risk in their exploitation through improved understanding of generically different reservoir types. These goals are to be accomplished by: 1) the creation of a large data base about geothermal reservoirs, 2) improved tools and methods for gathering data on geothermal reservoirs, and 3) modeling of reservoirs and utilization options. The NSF legacies are more research and training oriented, and the GREMP is geared primarily to the practical development of the geothermal reservoirs. 2 tabs., 3 figs.

  19. Predictions from the cloud: using data science to predict sports performance

    NARCIS (Netherlands)

    Blaauw, Frank; Emerencia, Armando Celino; den Hartigh, Jan Rudolf; Milovanović, Marko; Stoter, Inge; de Jonge, Peter

    2018-01-01

    In sport science, a major aim is to unravel the variables and parameters that influence sports performance. A key requirement for investigating these parameters is the availability of high quality data. More specifically, data that contains the variables of interest, and data that could be analyzed

  20. FRACTURED PETROLEUM RESERVOIRS

    Energy Technology Data Exchange (ETDEWEB)

    Abbas Firoozabadi

    1999-06-11

    The four chapters that are described in this report cover a variety of subjects that not only give insight into the understanding of multiphase flow in fractured porous media, but they provide also major contribution towards the understanding of flow processes with in-situ phase formation. In the following, a summary of all the chapters will be provided. Chapter I addresses issues related to water injection in water-wet fractured porous media. There are two parts in this chapter. Part I covers extensive set of measurements for water injection in water-wet fractured porous media. Both single matrix block and multiple matrix blocks tests are covered. There are two major findings from these experiments: (1) co-current imbibition can be more efficient than counter-current imbibition due to lower residual oil saturation and higher oil mobility, and (2) tight fractured porous media can be more efficient than a permeable porous media when subjected to water injection. These findings are directly related to the type of tests one can perform in the laboratory and to decide on the fate of water injection in fractured reservoirs. Part II of Chapter I presents modeling of water injection in water-wet fractured media by modifying the Buckley-Leverett Theory. A major element of the new model is the multiplication of the transfer flux by the fractured saturation with a power of 1/2. This simple model can account for both co-current and counter-current imbibition and computationally it is very efficient. It can be orders of magnitude faster than a conventional dual-porosity model. Part II also presents the results of water injection tests in very tight rocks of some 0.01 md permeability. Oil recovery from water imbibition tests from such at tight rock can be as high as 25 percent. Chapter II discusses solution gas-drive for cold production from heavy-oil reservoirs. The impetus for this work is the study of new gas phase formation from in-situ process which can be significantly

  1. EOS simulation and GRNN modeling of the constant volume depletion behavior of gas condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Elsharkawy, A.M.; Foda, S.G. [Kuwait University, Safat (Kuwait). Petroleum Engineering Dept.

    1998-03-01

    Currently, two approaches are being used to predict the changes in retrograde gas condensate composition and estimate the pressure depletion behavior of gas condensate reservoirs. The first approach uses the equation of states whereas the second uses empirical correlations. Equations of states (EOS) are poor predictive tools for complex hydrocarbon systems. The EOS needs adjustment against phase behavior data of reservoir fluid of known composition. The empirical correlation does not involve numerous numerical computations but their accuracy is limited. This study presents two general regression neural network (GRNN) models. The first model, GRNNM1, is developed to predict dew point pressure and gas compressibility at dew point using initial composition of numerous samples while the second model, GRNNM2, is developed to predict the changes in well stream effluent composition at any stages of pressure depletion. GRNNM2 can also be used to determine the initial reservoir fluid composition using dew point pressure, gas compressibility at dew point, and reservoir temperature. These models are based on analysis of 142 sample of laboratory studies of constant volume depletion (CVD) for gas condensate systems forming a total of 1082 depletion stages. The database represents a wide range of gas condensate systems obtained worldwide. The performance of the GRNN models has been compared to simulation results of the equation of state. The study shows that the proposed general regression neural network models are accurate, valid, and reliable. These models can be used to forecast CVD data needed for many reservoir engineering calculations in case laboratory data is unavailable. The GRNN models save computer time involved in EOS calculations. The study also show that once these models are properly trained they can be used to cut expenses of frequent sampling and laborious experimental CVD tests required for gas condensate reservoirs. 55 refs., 13 figs., 6 tabs.

  2. Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

    Science.gov (United States)

    Marques-Quinteiro, Pedro; Curral, Luís Alberto

    2012-01-01

    This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed.

  3. Petrofacies analysis - the petrophysical tool for geologic/engineering reservoir characterization

    Energy Technology Data Exchange (ETDEWEB)

    Watney, W.L.; Guy, W.J.; Gerlach, P.M. [Kansas Geological Survey, Lawrence, KS (United States)] [and others

    1997-08-01

    Petrofacies analysis is defined as the characterization and classification of pore types and fluid saturations as revealed by petrophysical measures of a reservoir. The word {open_quotes}petrofacies{close_quotes} makes an explicit link between petroleum engineers concerns with pore characteristics as arbiters of production performance, and the facies paradigm of geologists as a methodology for genetic understanding and prediction. In petrofacies analysis, the porosity and resistivity axes of the classical Pickett plot are used to map water saturation, bulk volume water, and estimated permeability, as well as capillary pressure information, where it is available. When data points are connected in order of depth within a reservoir, the characteristic patterns reflect reservoir rock character and its interplay with the hydrocarbon column. A third variable can be presented at each point on the crossplot by assigning a color scale that is based on other well logs, often gamma ray or photoelectric effect, or other derived variables. Contrasts between reservoir pore types and fluid saturations will be reflected in changing patterns on the crossplot and can help discriminate and characterize reservoir heterogeneity. Many hundreds of analyses of well logs facilitated by spreadsheet and object-oriented programming have provided the means to distinguish patterns typical of certain complex pore types for sandstones and carbonate reservoirs, occurrences of irreducible water saturation, and presence of transition zones. The result has been an improved means to evaluate potential production such as bypassed pay behind pipe and in old exploration holes, or to assess zonation and continuity of the reservoir. Petrofacies analysis is applied in this example to distinguishing flow units including discrimination of pore type as assessment of reservoir conformance and continuity. The analysis is facilitated through the use of color cross sections and cluster analysis.

  4. Predicting race performance in triathlon: the role of perfectionism, achievement goals, and personal goal setting.

    Science.gov (United States)

    Stoeber, Joachim; Uphill, Mark A; Hotham, Sarah

    2009-04-01

    The question of how perfectionism affects performance is highly debated. Because empirical studies examining perfectionism and competitive sport performance are missing, the present research investigated how perfectionism affected race performance and what role athletes' goals played in this relationship in two prospective studies with competitive triathletes (Study 1: N = 112; Study 2: N = 321). Regression analyses showed that perfectionistic personal standards, high performance-approach goals, low performance-avoidance goals, and high personal goals predicted race performance beyond athletes' performance level. Moreover, the contrast between performance-avoidance and performance-approach goals mediated the relationship between perfectionistic personal standards and performance, whereas personal goal setting mediated the relationship between performance-approach goals and performance. The findings indicate that perfectionistic personal standards do not undermine competitive performance, but are associated with goals that help athletes achieve their best possible performance.

  5. A human capital predictive model for agent performance in contact centres

    Directory of Open Access Journals (Sweden)

    Chris Jacobs

    2011-10-01

    Research purpose: The primary focus of this article was to develop a theoretically derived human capital predictive model for agent performance in contact centres and Business Process Outsourcing (BPO based on a review of current empirical research literature. Motivation for the study: The study was motivated by the need for a human capital predictive model that can predict agent and overall business performance. Research design: A nonempirical (theoretical research paradigm was adopted for this study and more specifically a theory or model-building approach was followed. A systematic review of published empirical research articles (for the period 2000–2009 in scholarly search portals was performed. Main findings: Eight building blocks of the human capital predictive model for agent performance in contact centres were identified. Forty-two of the human capital contact centre related articles are detailed in this study. Key empirical findings suggest that person– environment fit, job demands-resources, human resources management practices, engagement, agent well-being, agent competence; turnover intention; and agent performance are related to contact centre performance. Practical/managerial implications: The human capital predictive model serves as an operational management model that has performance implications for agents and ultimately influences the contact centre’s overall business performance. Contribution/value-add: This research can contribute to the fields of human resource management (HRM, human capital and performance management within the contact centre and BPO environment.

  6. Driving and Low Vision: Validity of Assessments for Predicting Performance of Drivers

    Science.gov (United States)

    Strong, J. Graham; Jutai, Jeffrey W.; Russell-Minda, Elizabeth; Evans, Mal

    2008-01-01

    The authors conducted a systematic review to examine whether vision-related assessments can predict the driving performance of individuals who have low vision. The results indicate that measures of visual field, contrast sensitivity, cognitive and attention-based tests, and driver screening tools have variable utility for predicting real-world…

  7. Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

    Science.gov (United States)

    Ye, Cheng; Biswas, Gautam

    2014-01-01

    Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…

  8. Predicting Story Goodness Performance from Cognitive Measures Following Traumatic Brain Injury

    Science.gov (United States)

    Le, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

    2012-01-01

    Purpose: This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Le, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. Method: One hundred…

  9. A Prediction Model for Community Colleges Using Graduation Rate as the Performance Indicator

    Science.gov (United States)

    Moosai, Susan

    2010-01-01

    In this thesis a prediction model using graduation rate as the performance indicator is obtained for community colleges for three cohort years, 2003, 2004, and 2005 in the states of California, Florida, and Michigan. Multiple Regression analysis, using an aggregate of seven predictor variables, was employed in determining this prediction model.…

  10. Numerical prediction of a bulb turbine performance hill chart through RANS simulations

    International Nuclear Information System (INIS)

    Guénette, V; Houde, S; Ciocan, G D; Deschênes, C; Dumas, G; Huang, J

    2012-01-01

    Within the framework of an international research consortium on low-head hydraulic turbine flow dynamics, the predictive behavior of Reynolds Averaged Navier-Stokes (RANS) simulations of the efficiency (η) hill chart of a bulb turbine is investigated. The paper presents the impacts of the blade tip gap and the hub gaps on performance predictions.

  11. Prediction of the aerodynamic performance of the Mexico rotor by using airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2013-01-01

    Blade Element Momentum (BEM) theory is a widely used technique for prediction of wind turbine aerodynamics performance, but the reliability of airfoil data is an important factor to improve the prediction accuracy of aerodynamic loads and power using a BEM code. The airfoil characteristics used...

  12. Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2014-01-01

    Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM...

  13. Hyperformance: predicting high-speed performance of a b-double

    CSIR Research Space (South Africa)

    Berman, Robert J

    2016-11-01

    Full Text Available of the vehicles. The prediction model bridges that gap in the form of a light-weight methodology to predict the PBS performance of a new vehicle design given a set of vehicle input data. Such a model was developed for typical South African 9-axle B-double PBS...

  14. Predicting Eight Grade Students' Equation Solving Performances via Concepts of Variable and Equality

    Science.gov (United States)

    Ertekin, Erhan

    2017-01-01

    This study focused on how two algebraic concepts- equality and variable- predicted 8th grade students' equation solving performance. In this study, predictive design as a correlational research design was used. Randomly selected 407 eight-grade students who were from the central districts of a city in the central region of Turkey participated in…

  15. A multi-source, multi-study investigation of job performance prediction by political skill

    DEFF Research Database (Denmark)

    Blickle, G.; Ferris, G.R.; Munyon, T.P.

    2011-01-01

    -sectional and longitudinal designs, this research tested the hypotheses that employee political skill, measured from the perspective of employees' assessor A, will positively predict job performance rated by assessor B (i.e. Hypothesis 1a), and vice versa, that employee political skill measured by assessor B will predict...

  16. The architecture of dynamic reservoir in the echo state network

    Science.gov (United States)

    Cui, Hongyan; Liu, Xiang; Li, Lixiang

    2012-09-01

    Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.

  17. Integrated reservoir characterization of a Posidonia Shale outcrop analogue: From serendipity to understanding

    NARCIS (Netherlands)

    Zijp, M.H.A.A.; Veen, J.H. ten; Verreussel, R.M.C.H.; Ventra, D.

    2014-01-01

    Shale gas reservoir stimulation procedures (e.g. hydraulic fracturing) require upfront prediction and planning that should be supported by a comprehensive reservoir characterization. Therefore, understanding shale depositional processes and associated vertical and lateral sedimentological

  18. Building Predictive Human Performance Models of Skill Acquisition in a Data Entry Task

    National Research Council Canada - National Science Library

    Fu, Wai-Tat; Gonzalez, Cleotilde; Healy, Alice F; Kole, James A; Bourne, Jr., Lyle E

    2006-01-01

    .... Since data entry is a central component in most human-machine interaction, a predictive model of performance will provide useful information that informs interface design and effectiveness of training...

  19. In vitro models for the prediction of in vivo performance of oral dosage forms

    NARCIS (Netherlands)

    Kostewicz, E.S.; Abrahamsson, B.; Brewster, M.; Brouwers, J.; Butler, J.; Carlert, S.; Dickinson, P.A.; Dressman, J.; Holm, R.; Klein, S.; Mann, J.; McAllister, M.; Minekus, M.; Muenster, U.; Müllertz, A.; Verwei, M.; Vertzoni, M.; Weitschies, W.; Augustijns, P.

    2014-01-01

    Accurate prediction of the in vivo biopharmaceutical performance of oral drug formulations is critical to efficient drug development. Traditionally, in vitro evaluation of oral drug formulations has focused on disintegration and dissolution testing for quality control (QC) purposes. The connection

  20. Biological lifestyle factors in adult distance education: predicting cognitive and learning performance

    NARCIS (Netherlands)

    Gijselaers, Jérôme

    2015-01-01

    Gijselaers, H. J. M. (2015, 20 October). Biological lifestyle factors in adult distance education: predicting cognitive and learning performance. Presentation given for the inter-faculty Data Science group at the Open University of the Netherlands, Heerlen, The Netherlands.

  1. Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test.

    Science.gov (United States)

    Ring, Patrick; Neyse, Levent; David-Barett, Tamas; Schmidt, Ulrich

    2016-01-01

    This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT) and whether they differ by gender. After participants completed the CRT, they predicted their own (i), the other participants' (ii), men's (iii), and women's (iv) number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women's predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one's ability relative to same and opposite sex peers.

  2. Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test

    Directory of Open Access Journals (Sweden)

    Patrick Ring

    2016-11-01

    Full Text Available This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT and whether they differ by gender. After participants completed the CRT, they predicted their own (i, the other participants’ (ii, men’s (iii, and women’s (iv number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women’s predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one’s ability relative to same and opposite sex peers.

  3. Mean streamline analysis for performance prediction of cross-flow fans

    International Nuclear Information System (INIS)

    Kim, Jae Won; Oh, Hyoung Woo

    2004-01-01

    This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans

  4. When bad stress goes good: increased threat reactivity predicts improved category learning performance.

    Science.gov (United States)

    Ell, Shawn W; Cosley, Brandon; McCoy, Shannon K

    2011-02-01

    The way in which we respond to everyday stressors can have a profound impact on cognitive functioning. Maladaptive stress responses in particular are generally associated with impaired cognitive performance. We argue, however, that the cognitive system mediating task performance is also a critical determinant of the stress-cognition relationship. Consistent with this prediction, we observed that stress reactivity consistent with a maladaptive, threat response differentially predicted performance on two categorization tasks. Increased threat reactivity predicted enhanced performance on an information-integration task (i.e., learning is thought to depend upon a procedural-based memory system), and a (nonsignificant) trend for impaired performance on a rule-based task (i.e., learning is thought to depend upon a hypothesis-testing system). These data suggest that it is critical to consider both variability in the stress response and variability in the cognitive system mediating task performance in order to fully understand the stress-cognition relationship.

  5. Prediction of Rowing Ergometer Performance from Functional Anaerobic Power, Strength and Anthropometric Components

    Directory of Open Access Journals (Sweden)

    Akça Firat

    2014-07-01

    Full Text Available The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE. Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s. Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s. As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.

  6. User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.

    Science.gov (United States)

    Ahn, Minkyu; Cho, Hohyun; Ahn, Sangtae; Jun, Sung C

    2018-01-01

    Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation ( r = 0.64, p performance even without feedback information. This implies that the human brain is an active learning system and, by self-experiencing the endogenous motor imagery process, it can sense and adopt the quality of the process. Thus, it is believed that users may be able to predict MI-BCI performance and results may contribute to a better understanding of low performance and advancing BCI.

  7. Quantifying characteristic growth dynamics in a semiarid grassland ecosystem by predicting short-term NDVI phenology from daily rainfall: a simple 4 parameter coupled-reservoir model

    Science.gov (United States)

    Predicting impacts of the magnitude and seasonal timing of rainfall pulses in water-limited grassland ecosystems concerns ecologists, climate scientists, hydrologists, and a variety of stakeholders. This report describes a simple, effective procedure to emulate the seasonal response of grassland bio...

  8. Sediment management for reservoir

    International Nuclear Information System (INIS)

    Rahman, A.

    2005-01-01

    All natural lakes and reservoirs whether on rivers, tributaries or off channel storages are doomed to be sited up. Pakistan has two major reservoirs of Tarbela and Managla and shallow lake created by Chashma Barrage. Tarbela and Mangla Lakes are losing their capacities ever since first impounding, Tarbela since 1974 and Mangla since 1967. Tarbela Reservoir receives average annual flow of about 62 MAF and sediment deposits of 0.11 MAF whereas Mangla gets about 23 MAF of average annual flows and is losing its storage at the rate of average 34,000 MAF annually. The loss of storage is a great concern and studies for Tarbela were carried out by TAMS and Wallingford to sustain its capacity whereas no study has been done for Mangla as yet except as part of study for Raised Mangla, which is only desk work. Delta of Tarbala reservoir has advanced to about 6.59 miles (Pivot Point) from power intakes. In case of liquefaction of delta by tremor as low as 0.12g peak ground acceleration the power tunnels I, 2 and 3 will be blocked. Minimum Pool of reservoir is being raised so as to check the advance of delta. Mangla delta will follow the trend of Tarbela. Tarbela has vast amount of data as reservoir is surveyed every year, whereas Mangla Reservoir survey was done at five-year interval, which has now been proposed .to be reduced to three-year interval. In addition suspended sediment sampling of inflow streams is being done by Surface Water Hydrology Project of WAPDA as also some bed load sampling. The problem of Chasma Reservoir has also been highlighted, as it is being indiscriminately being filled up and drawdown several times a year without regard to its reaction to this treatment. The Sediment Management of these reservoirs is essential and the paper discusses pros and cons of various alternatives. (author)

  9. Neither here, nor there: impression management does not predict expatriate adjustment and job performance

    OpenAIRE

    HANNAH JACKSON FOLDES; DENIZ S. ONES; HANDAN KEPIR SINANGIL

    2006-01-01

    Social desirability scale scores reflect substantive individual differences related to personality. The objective of the current study was to examine whether social desirability, and impression management specifically (a component of social desirability), is predictive of adjustment and job performance for expatriates. Based on theoretical considerations, it was proposed that impression management might be linked to expatriate job performance in a predictive and mediated relationship through ...

  10. Comparative values of medical school assessments in the prediction of internship performance.

    Science.gov (United States)

    Lee, Ming; Vermillion, Michelle

    2018-02-01

    Multiple undergraduate achievements have been used for graduate admission consideration. Their relative values in the prediction of residency performance are not clear. This study compared the contributions of major undergraduate assessments to the prediction of internship performance. Internship performance ratings of the graduates of a medical school were collected from 2012 to 2015. Hierarchical multiple regression analyses were used to examine the predictive values of undergraduate measures assessing basic and clinical sciences knowledge and clinical performances, after controlling for differences in the Medical College Admission Test (MCAT). Four hundred eighty (75%) graduates' archived data were used in the study. Analyses revealed that clinical competencies, assessed by the USMLE Step 2 CK, NBME medicine exam, and an eight-station objective structured clinical examination (OSCE), were strong predictors of internship performance. Neither the USMLE Step 1 nor the inpatient internal medicine clerkship evaluation predicted internship performance. The undergraduate assessments as a whole showed a significant collective relationship with internship performance (ΔR 2  = 0.12, p < 0.001). The study supports the use of clinical competency assessments, instead of pre-clinical measures, in graduate admission consideration. It also provides validity evidence for OSCE scores in the prediction of workplace performance.

  11. Optimising reservoir operation

    DEFF Research Database (Denmark)

    Ngo, Long le

    Anvendelse af optimeringsteknik til drift af reservoirer er blevet et væsentligt element i vandressource-planlægning og -forvaltning. Traditionelt har reservoirer været styret af heuristiske procedurer for udtag af vand, suppleret i en vis udstrækning af subjektive beslutninger. Udnyttelse af...... reservoirer involverer en lang række interessenter med meget forskellige formål (f.eks. kunstig vanding, vandkraft, vandforsyning mv.), og optimeringsteknik kan langt bedre lede frem til afbalancerede løsninger af de ofte modstridende interesser. Afhandlingen foreslår en række tiltag, hvormed traditionelle...

  12. Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Chien-Ho Ko

    2013-01-01

    Full Text Available Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs, Fuzzy Logic (FL, and Neural Networks (NNs. FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  13. Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

    Science.gov (United States)

    Ko, Chien-Ho

    2013-01-01

    Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NNs). FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  14. Predicting space telerobotic operator training performance from human spatial ability assessment

    Science.gov (United States)

    Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

    2013-11-01

    Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

  15. MIKROMITSETY- MIGRANTS IN MINGECHEVIR RESERVOIR

    Directory of Open Access Journals (Sweden)

    M. A. Salmanov

    2017-01-01

    Full Text Available Aim. It is hardly possible to predict the continued stability of the watercourse ecosystems without the study of biological characteristics and composition of organisms inhabiting them. In the last 35-40 years, environmental conditions of the Mingachevir reservoir are determined by the stationary anthropogenic pressure. It was found that such components of plankton as algae, bacteria and fungi play a leading role in the transformation and migration of pollutants. The role of the three groups of organisms is very important in maintaining the water quality by elimination of pollutants. Among the organisms inhabiting the Mingachevir Reservoir, micromycetes have not yet been studied. Therefore, the study of the species composition and seasonal dynamics, peculiarities of their growth and development in the environment with the presence of some of the pollutants should be considered to date.Methods. In order to determine the role of micromycetes-migrants in the mineralization of organic substrates, as an active participant of self-purification process, we used water samples from the bottom sediments as well as decaying and skeletonized stalks of cane, reeds, algae, macrophytes, exuvia of insects and fish remains submerged in water.Findings. For the first time, we obtained the data on the quality and quantity of microscopic mycelial fungi in freshwater bodies on the example of the Mingachevir water reservoir; we also studied the possibilities for oxygenating the autochthonous organic matter of allochthonous origin with micromycetes-migrants.Conclusions. It was found that the seasonal development of micromycetes-migrants within the Mingachevir reservoir is characterized by an increase in the number of species in the summer and a gradual reduction in species diversity in the fall. 

  16. Model to predict the flow of tracers in naturally fractured geothermal reservoirs; Modelo para predecir el flujo de trazadores en yacimientos geotermicos naturalmente fracturados

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez Sabag, Jetzabeth

    1988-02-01

    The proposed model has been developed to study the flow of tracers through naturally fractured geothermal reservoirs.