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Sample records for reservoir performance predictions

  1. TRITIUM RESERVOIR STRUCTURAL PERFORMANCE PREDICTION

    Energy Technology Data Exchange (ETDEWEB)

    Lam, P.S.; Morgan, M.J

    2005-11-10

    The burst test is used to assess the material performance of tritium reservoirs in the surveillance program in which reservoirs have been in service for extended periods of time. A materials system model and finite element procedure were developed under a Savannah River Site Plant-Directed Research and Development (PDRD) program to predict the structural response under a full range of loading and aged material conditions of the reservoir. The results show that the predicted burst pressure and volume ductility are in good agreement with the actual burst test results for the unexposed units. The material tensile properties used in the calculations were obtained from a curved tensile specimen harvested from a companion reservoir by Electric Discharge Machining (EDM). In the absence of exposed and aged material tensile data, literature data were used for demonstrating the methodology in terms of the helium-3 concentration in the metal and the depth of penetration in the reservoir sidewall. It can be shown that the volume ductility decreases significantly with the presence of tritium and its decay product, helium-3, in the metal, as was observed in the laboratory-controlled burst tests. The model and analytical procedure provides a predictive tool for reservoir structural integrity under aging conditions. It is recommended that benchmark tests and analysis for aged materials be performed. The methodology can be augmented to predict performance for reservoir with flaws.

  2. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Martin J.; Orr, Jr., Franklin M.

    1999-12-20

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1998 - September 1998 under the third year of a three-year Department of Energy (DOE) grant 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 research is divided into four main 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.

  3. PREDICTION OF GAS INJECTION PERFORMANCE FOR HETEROGENEOUS RESERVOIRS

    Energy Technology Data Exchange (ETDEWEB)

    Martin J. Blunt; Franklin M. Orr Jr

    2000-06-01

    This final report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1996--May 2000 under a three-year grant from the Department of Energy on the ''Prediction of Gas Injection Performance for Heterogeneous Reservoirs''. The advances from the research include: new tools for streamline-based simulation including the effects of gravity, changing well conditions, and compositional displacements; analytical solutions to 1D compositional displacements which can speed-up gas injection simulation still further; and modeling and experiments that delineate the physics that is unique to three-phase flow.

  4. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Franklin M. Orr, Jr; Martin J. Blunt

    1998-03-31

    This project performs research in four main areas: laboratory experiments to measure three-phase relative permeability; network modeling to predict three-phase relative perme- ability; benchmark simulations of gas injection and waterfl ooding at the field scale; and the development of fast streamline techniques to study field-scale oil. The aim of the work is to achieve a comprehensive description of gas injection processes from the pore to the core to the reservoir scale. In this report we provide a detailed description of our measurements of three-phase relative permeability.

  5. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Michael J.; Orr, Franklin M.

    1999-05-26

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1996 - September 1997 under the first year of a three-year Department of Energy grant 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 main 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 stage 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Franklin M. Orr, Jr.

    2002-06-30

    This report outlines progress in the third quarter of the second year of the DOE project ''High Resolution Prediction of Gas Injection Process Performance for Heterogeneous Reservoirs''. High order finite difference schemes for one-dimensional, two-phase, multicomponent displacements are investigated. Numerical tests are run using a three component fluid description for a case when the interaction between phase behavior and flow is strong. Some currently used total variation diminishing (TVD) methods produce unstable results. A third order essentially non-oscillatory (ENO) method captures the effects of phase behavior for this test case. Possible modifications to ensure stability are discussed along with plans to incorporate higher order schemes into the 3DSL streamline simulator.

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

    Energy Technology Data Exchange (ETDEWEB)

    Franklin M. Orr, Jr.

    2001-12-31

    This report outlines progress in the first quarter of the second year of the DOE project ''High Resolution Prediction of Gas Injection Process Performance for Heterogeneous Reservoirs''. The application of the analytical theory for gas injection processes, including the effects of volume change on mixing, has up to now been limited to fully self-sharpening systems, systems where all solution segments that connect the key tie lines present in the displacement are shock fronts. In the following report, we describe the extension of the analytical theory to include systems with rarefactions (continuous composition and saturation variations) between key tie lines. With the completion of this analysis, a completely general procedure has been developed for finding solutions for problems in which a multicomponent gas displaces a multicomponent oil.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  13. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Franklin M. Orr, Jr.

    2003-06-30

    This report presents a detailed analysis of the development of miscibility during gas cycling in condensates and the formation of condensate banks at the leading edge of the displacement front. Dispersion-free, semi-analytical one-dimensional (1D) calculations are presented for enhanced condensate recovery by gas injection. The semi-analytical approach allows investigation of the possible formation of condensate banks (often at saturations that exceed the residual liquid saturation) and also allows fast screening of optimal injection gas compositions. We describe construction of the semi-analytical solutions, a process which differs in some ways from related displacements for oil systems. We use an analysis of key equilibrium tie lines that are part of the displacement composition path to demonstrate that the mechanism controlling the development of miscibility in gas condensates may vary from first-contact miscible drives to pure vaporizing and combined vaporizing/condensing drives. Depending on the compositions of the condensate and the injected gas, multicontact miscibility can develop at the dew point pressure, or below the dew point pressure of the reservoir fluid mixture. Finally, we discuss the possible impact on performance prediction of the formation of a mobile condensate bank at the displacement front in near-miscible gas cycling/injection schemes.

  15. A numerical/empirical technique for history matching and predicting cyclic steam performance in Canadian oil sands reservoirs

    Science.gov (United States)

    Leshchyshyn, Theodore Henry

    correlation curves. The key reservoir property used to develop a specific curve was to vary the initial mobile water saturation. Individual pilot wells were then history-matched using these correlation curves, adjusting for thermal net pay using perforation height and a fundamentally derived "net pay factor". Operating days (injection plus production) were required to complete the history matching calculations. Subsequent cycles were then history-matched by applying an Efficiency Multiplication Factor (EMF) to the original first cycle prediction method as well as selecting the proper correlation curve for the specific cycle under analysis by using the appropriate steam injection rates and slug sizes. History matches were performed on eight PHOP wells (two back-to-back, five-spot patterns) completed in the Wabiskaw and, three single-well tests completed just below in the McMurray Formation. Predictions for the PHOP Wabiskaw Formation first cycle bitumen production averaged within 1% of the actual pilot total. Bitumen recovery from individual wells for second cycle onwards, was within 20% of actual values. For testing the correlations, matching was also performed on cyclic steam data from British Petroleum's Wolf Lake Project, the Esso Cold Lake Project, and the PCEJ Fort McMurray Pilot, a joint venture of Petro-Canada, Cities Services (Canadian Occidental), Esso, and Japan-Canada Oil Sands with reasonable results.

  16. Hydrological ensemble predictions for reservoir inflow management

    Science.gov (United States)

    Zalachori, Ioanna; Ramos, Maria-Helena; Garçon, Rémy; Gailhard, Joel

    2013-04-01

    Hydrologic forecasting is a topic of special importance for a variety of users with different purposes. It concerns operational hydrologists interested in forecasting hazardous events (eg., floods and droughts) for early warning and prevention, as well as planners and managers searching to optimize the management of water resources systems at different space-time scales. The general aim of this study is to investigate the benefits of using hydrological ensemble predictions for reservoir inflow management. Ensemble weather forecasts are used as input to a hydrologic forecasting model and daily ensemble streamflow forecasts are generated up to a lead time of 7 days. Forecasts are then integrated into a heuristic decision model for reservoir management procedures. Performance is evaluated in terms of potential gain in energy production. The sensitivity of the results to various reservoir characteristics and future streamflow scenarios is assessed. A set of 11 catchments in France is used to illustrate the added value of ensemble streamflow forecasts for reservoir management.

  17. 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.

  18. 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

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

    Directory of Open Access Journals (Sweden)

    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

  20. Nonlinear Model Predictive Control for Oil Reservoirs Management

    DEFF Research Database (Denmark)

    Capolei, Andrea

    . The controller consists of -A model based optimizer for maximizing some predicted financial measure of the reservoir (e.g. the net present value). -A parameter and state estimator. -Use of the moving horizon principle for data assimilation and implementation of the computed control input. The optimizer uses...... Optimization has been suggested to compensate for inherent geological uncertainties in an oil field. In robust optimization of an oil reservoir, the water injection and production borehole pressures are computed such that the predicted net present value of an ensemble of permeability field realizations...... 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...

  1. 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

  2. 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.

  3. 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.

  4. Central aortic reservoir-wave analysis improves prediction of cardiovascular events in elderly hypertensives.

    Science.gov (United States)

    Narayan, Om; Davies, Justin E; Hughes, Alun D; Dart, Anthony M; Parker, Kim H; Reid, Christopher; Cameron, James D

    2015-03-01

    Several morphological parameters based on the central aortic pressure waveform are proposed as cardiovascular risk markers, yet no study has definitively demonstrated the incremental value of any waveform parameter in addition to currently accepted biomarkers in elderly, hypertensive patients. The reservoir-wave concept combines elements of wave transmission and Windkessel models of arterial pressure generation, defining an excess pressure superimposed on a background reservoir pressure. The utility of pressure rate constants derived from reservoir-wave analysis in prediction of cardiovascular events is unknown. Carotid blood pressure waveforms were measured prerandomization in a subset of 838 patients in the Second Australian National Blood Pressure Study. Reservoir-wave analysis was performed and indices of arterial function, including the systolic and diastolic rate constants, were derived. Survival analysis was performed to determine the association between reservoir-wave parameters and cardiovascular events. The incremental utility of reservoir-wave parameters in addition to the Framingham Risk Score was assessed. Baseline values of the systolic rate constant were independently predictive of clinical outcome (hazard ratio, 0.33; 95% confidence interval, 0.13-0.82; P=0.016 for fatal and nonfatal stroke and myocardial infarction and hazard ratio, 0.38; 95% confidence interval, 0.20-0.74; P=0.004 for the composite end point, including all cardiovascular events). Addition of this parameter to the Framingham Risk Score was associated with an improvement in predictive accuracy for cardiovascular events as assessed by the integrated discrimination improvement and net reclassification improvement indices. This analysis demonstrates that baseline values of the systolic rate constant predict clinical outcomes in elderly patients with hypertension and incrementally improve prognostication of cardiovascular events. © 2014 American Heart Association, Inc.

  5. Performance of one of the Iranian carbonate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Jamshidnezhad, M. [National Iranian Oil Co. (Iran, Islamic Republic of)

    2002-07-01

    The performance of a horizontal well in a carbonate petroleum reservoir in Iran was described following an analysis of of an Iranian carbonate field located in southern Iran. The field is 23 km long, 7 km wide and contains 2 reservoirs, one of which sits over the other. An impermeable zone separates the 2 reservoirs. Both horizontal and directional drilling technologies have been used to develop the field. Production began a decade ago and is expected to continue for another 80 years. Currently, there are 28 wells, of which 6 are horizontal and 7 are directional. There are several problems regarding horizontal wells in the carbonate reservoirs of Iran. These include the loss of drilling mud, difficulty in petrophysical logging, and high costs. This study included a geological examination of PVT, static pressure, well testing, and experimental performance of horizontal, vertical and directional wells to determine the overall performance of the field. The objective was to find ways to increase the rate of production. It was determined that wells should be drilled vertically as much as possible, particularly in the second reservoir. Horizontal drilling technology should be used a last resort and only in the first reservoir. The author also recommends the use of an artificial lift involving electrical submersible pumps. 1 ref., 4 tabs., 10 figs.

  6. A Novel Method for Performance Analysis of Compartmentalized Reservoirs

    Directory of Open Access Journals (Sweden)

    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

  7. 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.

  8. Simulation studies to evaluate the effect of fracture closure on the performance of fractured reservoirs; Final report

    Energy Technology Data Exchange (ETDEWEB)

    Howrie, I.; Dauben, D.

    1994-03-01

    A three-year research program to evaluate the effect of fracture closure on the recovery of oil and gas from naturally fractured reservoirs has been completed. The overall objectives of the study were to: (1) evaluate the reservoir conditions for which fracture closure is significant, and (2) evaluate innovative fluid injection techniques capable of maintaining pressure within the reservoir. The evaluations of reservoir performance were made by a modern dual porosity simulator, TETRAD. This simulator treats both porosity and permeability as functions of pore pressure. The Austin Chalk in the Pearsall Field in of South Texas was selected as the prototype fractured reservoir for this work. During the first year, simulations of vertical and horizontal well performance were made assuming that fracture permeability was insensitive to pressure change. Sensitivity runs indicated that the simulator was predicting the effects of critical reservoir parameters in a logical and consistent manner. The results confirmed that horizontal wells could increase both rate of oil recovery and total oil recovery from naturally fractured reservoirs. In the second year, the performance of the same vertical and horizontal wells was reevaluated with fracture permeability treated as a function of reservoir pressure. To investigate sensitivity to in situ stress, differing loading conditions were assumed. Simulated natural depletions confirm that pressure sensitive fractures degrade well performance. The severity of degradation worsens when the initial reservoir pressure approaches the average stress condition of the reservoir, such as occurs in over pressured reservoirs. Simulations with water injection indicate that degradation of permeability can be counteracted when reservoir pressure is maintained and oil recovery can be increased when reservoir properties are favorable.

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

    Energy Technology Data Exchange (ETDEWEB)

    Mohan Kelkar

    2003-10-01

    increases, the remaining oil saturation decreases. This is evident from log and core analysis. (5) Using a compositional simulator, we are able to reproduce the important reservoir characteristics by assuming a two layer model. One layer is high permeability region containing water and the other layer is low permeability region containing mostly oil. The results are further verified by using a dual porosity model. Assuming that most of the volatile oil is contained in the matrix and the water is contained in the fractures, we are able to reproduce important reservoir performance characteristics. (6) Evaluation of secondary mechanisms indicates that CO{sub 2} flooding is potentially a viable option if CO{sub 2} is available at reasonable price. We have conducted detailed simulation studies to verify the effectiveness of CO{sub 2} huff-n-puff process. We are in the process of conducting additional lab tests to verify the efficacy of the same displacement. (7) Another possibility of improving the oil recovery is to inject surfactants to change the near well bore wettability of the rock from oil wet to water wet. By changing the wettability, we may be able to retard the water flow and hence improve the oil recovery as a percentage of total fluid produced. If surfactant is reasonably priced, other possibility is also to use huff-n-puff process using surfactants. Laboratory experiments are promising, and additional investigation continues. (8) Preliminary economic evaluation indicates that vertical wells outperform horizontal wells. Future work in the project would include: (1) Build multi-well numerical model to reproduce overall reservoir performance rather than individual well performance. Special emphasis will be placed on hydrodynamic connectivity between wells. (2) Collect data from adjacent Hunton reservoirs to validate our understanding of what makes it a productive reservoir. (3) Develop statistical methods to rank various reservoirs in Hunton formation. This will allow

  10. 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.

  11. 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.

  12. 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

  13. 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.

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

    Indian Academy of Sciences (India)

    cations such as flood control, drought manage- ment, optimal reservoir operation and hydropower generation. There are many studies pertaining to .... est, 49% cultivated area, 6% waste land and 4% of others (CDO 1992). The water spread area at full reservoir level is 115.36 km2 which is about 13% of the total catchment ...

  15. Producing Gas-Oil Ratio Performance of Conventional and Unconventional Reservoirs

    OpenAIRE

    Lei, Guowen

    2012-01-01

    This study presents a detailed analysis of producing gas-oil ratio performance characteristics from conventional reservoir to unconventional reservoir. Numerical simulations of various reservoir fluid systems are included for comparison. In a wide sense of the word, the term of unconventional reservoir is including tight gas sand, coal bed methane, gas hydrate deposits, heavy oil gas shale and etc. In this study we specify the unconventional reservoir to only mean the low and ultra low permea...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2002-06-15

    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.

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. Prediction of mill performance

    Energy Technology Data Exchange (ETDEWEB)

    P.A. Bennett [CoalTech Pty Ltd. (Australia)

    2005-07-01

    This Australian Coal Association Research Program (ACARP) project aimed to demonstrate that the Hardgrove Grindability Index (HGI) coupled with standard Petrographic Analysis can be used to greatly improve the prediction of mill power requirements, mill throughput and product size. The project examined the mill test data from ACIRL's pilot scale vertical spindle mill on 96 coals. A total of 360 mill tests, conducted under a wide range of throughputs, roll pressures and classifier settings, were included into the data set. The mill performance of maceral groups or microlithotypes was assumed to be additive, that is, each maceral group or microlithotype behaved independently and a size fraction of the product PF was the volume weighted sum of the petrographic components of that size fraction. Based on this assumption it was possible to determine the size distribution of the product PF, for a wide range of milling conditions, based solely on petrographic analysis. Microlithotypes were not determined directly but were estimated from the maceral analysis. The size distribution of individual maceral groups or microlithotypes can also be estimated based on developed correlations. Size distribution determined from petrographic analysis proved to be a better estimate than that determined from the HGI. Mill power can be estimated from petrographic analysis, but the HGI was found to be a better predictor of mill power. 19 refs., 4 figs., 1 tab.

  2. Prediction of diagenesis and reservoir quality using wireline logs ...

    African Journals Online (AJOL)

    Reservoir quality is mainly controlled by environment deposit type and diagenesis processes. To investigate such subject we usually proceed to microscopic techniques. Absence of outcrops and missing of core samples let us use conventional wireline logs and core lab measurements as primary data. Direct lecture of well ...

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

    Indian Academy of Sciences (India)

    In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the applicability and effect of using lumped and distributed input data in MLR approach, Koyna river watershed in Maharashtra, India is chosen as a case study. The results are also ...

  4. pressure analysis and fluid contact prediction for alpha reservoir

    African Journals Online (AJOL)

    HOD

    1, 3, CENTER OF EXCELLENCE IN INTEGRATED PETROLEUM EXPLORATION AND EVALUATION STUDIES (IPEES),UNIVERSITY. OF BENIN, BENIN ... economic value of the asset. Early oil rim development can be negatively impacted by water coning and/or early gas breakthrough.[1].Oil rim reservoirs are common in.

  5. Performance Analysis of Fractured Wells with Stimulated Reservoir Volume in Coal Seam Reservoirs

    Directory of Open Access Journals (Sweden)

    Yu-long Zhao

    2016-01-01

    Full Text Available CoalBed Methane (CBM, as one kind of unconventional gas, is an important energy resource, attracting industry interest in research and development. Using the Langmuir adsorption isotherm, Fick’s law in the matrix and Darcy flow in cleat fractures, and treating the Stimulated Reservoir Volume (SRV induced by hydraulic fracturing as a radial composite model, the continuous linear source function with constant production is derived by the methods of the Laplace transform and Duhamel theory. Based on the linear source function, semi-analytical solutions are obtained for a fractured vertical well producing at a constant production rate or constant bottom-hole pressure. With the help of the Stehfest numerical algorithm and computer programing, the well test and rate decline type curves are obtained, and the key flow regimes of fractured CBM wells are: wellbore storage, linear flow in SRV region, diffusion flow and later pseudo-radial flow. Finally, we analyze the effect of various parameters, such as the Langmuir volume, radius and permeability in the SRV region, on the production performance. The research results concluded in this paper have significant importance in terms of the development, well test interpretations and production performance analysis of unconventional gas.

  6. 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

  7. A snow and ice melt seasonal prediction modelling system for Alpine reservoirs

    Science.gov (United States)

    Förster, Kristian; Oesterle, Felix; Hanzer, Florian; Schöber, Johannes; Huttenlau, Matthias; Strasser, Ulrich

    2016-10-01

    The timing and the volume of snow and ice melt in Alpine catchments are crucial for management operations of reservoirs and hydropower generation. Moreover, a sustainable reservoir operation through reservoir storage and flow control as part of flood risk management is important for downstream communities. Forecast systems typically provide predictions for a few days in advance. Reservoir operators would benefit if lead times could be extended in order to optimise the reservoir management. Current seasonal prediction products such as the NCEP (National Centers for Environmental Prediction) Climate Forecast System version 2 (CFSv2) enable seasonal forecasts up to nine months in advance, with of course decreasing accuracy as lead-time increases. We present a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps (Gepatschalm). Meteorological forecasts are obtained from the CFSv2 model. Subsequently, these data are downscaled to the Alpine Water balance And Runoff Estimation model AWARE running at monthly time step. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN that predicts hourly fields of snow water equivalent and snowmelt at a regular grid with 50 m spacing. Reservoir inflow is calculated taking into account various runs of the CFSv2 model. These simulations are compared with observed inflow volumes for the melting and accumulation period 2015.

  8. 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

  9. 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

  10. Predicting Academic Performance

    OpenAIRE

    Marcos Gallacher

    2005-01-01

    This paper discussed advantages and disadvantages associated with the use of "admission tests" as predictors of performance in undergraduate studies programs. The paper analyzes performance of economics and business administration students. This performance is linked to admission tests results. The paper also analyzes aspects of performance related to (i) differential progress through time, and (ii) differences in the extent to which students have "areas of interest/ability". The paper conclu...

  11. 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.

  12. 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)

  13. 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.

  14. 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.

  15. Performance of the large-reservoir oxygen mask (Ventimask).

    Science.gov (United States)

    Jones, H A; Turner, S L; Hughes, J M

    1984-06-30

    The performance of large-reservoir Venturi masks ('Ventimask') giving nominal inspired oxygen (O2) concentrations ranging from 24% to 60% was assessed in a face model, in six normal subjects, and in ten patients with severe chronic airflow obstruction at the O2 flow rates recommended. Instantaneous oxygen concentrations were measured with a mass spectrometer ('Centronics MGA200') and volume-weighted to give mean inspired concentrations (FiO2). In human studies volume-weighting was achieved by simultaneous measurement of tidal volume from chest and abdominal motion by the use of a respiratory inductance plethysmograph ('Respitrace'). Reinspiration of dead space from the mask was assessed by measuring FiCO2, which varied from 0.2 to 0.4% (normals) and was 0.6 +/- 0.4% in patients. In normal subjects and patients breathing at rest the FiO2% in 24, 28, 35, and 40% ventimasks was within 1.9% absolute of nominal (range-1.2 to +1.9%) but the 60% mask read low (50.3%). Various factors can make FiO2 less than nominal but the human and model studies indicated that reinspiration of dead space from the mask was more important than hyperventilation. In tachypnoeic patients (frequency greater than 30/min), the O2 flow should be increased to 50% above recommended.

  16. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1)

    Energy Technology Data Exchange (ETDEWEB)

    Watney, W.L.

    1992-01-01

    Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.

  17. Adjustment and prediction of primary behavior of some reservoirs in the Cinco Presidentes field (Mexico)

    Energy Technology Data Exchange (ETDEWEB)

    Zamora, F.C.P.; Mendoza, J.S.

    1974-03-01

    The primary behavior of some reservoirs of the Cinco Presidentes field is analyzed. These are reservoirs in the final stage of exploitation, in which a great decline of pressure and of production has been observed. The principal aspect of the study consists in having carried out, in spite of the scarcity of information, an adjustment that permitted a prediction of behavior. Because of the small amount of bottom-hole pressure information available, the adjustment is basically made as a function of the production data, especially studying the variation of cumulative production of gas with respect to that of oil. This article shows that many times, because of the insufficiency of data, reservoir behavior is evaluated within a very small probability range, and sets out a foundation for insisting on obtaining information, short-and long-term, in reservoir engineering.

  18. 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.

  19. Geothermal Project Den Haag - 3-D models for temperature prediction and reservoir characterization

    Science.gov (United States)

    Mottaghy, D.; Pechnig, R.; Willemsen, G.; Simmelink, H. J.; Vandeweijer, V.

    2009-04-01

    In the framework of the "Den Haag Zuidwest" geothermal district heating system a deep geothermal installation is projected. The target horizon of the planned doublet is the "Delft sandstone" which has been extensively explored for oil- and gas reservoirs in the last century. In the target area, this upper Jurassic sandstone layer is found at a depth of about 2300 m with an average thickness of about 50 m. The study presented here focuses on the prediction of reservoir temperatures and production behavior which is crucial for planning a deep geothermal installation. In the first phase, the main objective was to find out whether there is a significant influence of the 3-dimensional structures of anticlines and synclines on the temperature field, which could cause formation temperatures deviating from the predicted extrapolated temperature data from oil and gas exploration wells. To this end a regional model was set up as a basis for steady state numerical simulations. Since representative input parameters are decisive for reliable model results, all available information was compiled: a) the subsurface geometry, depth and thickness of the stratigraphic layers known from seismic data sets 2) borehole geophysical data and c) geological and petrographical information from exploration wells. In addition 50 cuttings samples were taken from two selected key wells in order to provide direct information on thermal properties of the underlying strata. Thermal conductivity and rock matrix density were measured in the laboratory. These data were combined with a petrophysical log analysis (Gamma Ray, Sonic, Density and Resistivity), which resulted in continuous profiles of porosity, effective thermal conductivity and radiogenetic heat production. These profiles allowed to asses in detail the variability of the petrophysical properties with depth and to check for lateral changes between the wells. All this data entered the numerical simulations which were performed by a 3-D

  20. 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

  1. 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

  2. Shale Gas Geomechanics for Development and Performance of Unconventional Reservoirs

    Science.gov (United States)

    Domonik, Andrzej; Łukaszewski, Paweł; Wilczyński, Przemysław; Dziedzic, Artur; Łukasiak, Dominik; Bobrowska, Alicja

    2017-04-01

    Mechanical properties of individual shale formations are predominantly determined by their lithology, which reflects sedimentary facies distribution, and subsequent diagenetic and tectonic alterations. Shale rocks may exhibit complex elasto-viscoplastic deformation mechanisms depending on the rate of deformation and the amount of clay minerals, also bearing implications for subcritical crack growth and heterogeneous fracture network development. Thus, geomechanics for unconventional resources differs from conventional reservoirs due to inelastic matrix behavior, stress sensitivity, rock anisotropy and low matrix permeability. Effective horizontal drilling and hydraulic fracturing technologies are required to obtain and maintain high performance. Success of these techniques strongly depends on the geomechanical investigations of shales. An inelastic behavior of shales draws increasing attention of investigators [1], due to its role in stress relaxation between fracturing phases. A strong mechanical anisotropy in the vertical plane and a lower and more variable one in the horizontal plane are characteristic for shale rocks. The horizontal anisotropy plays an important role in determining the direction and effectiveness of propagation of technological hydraulic fractures. Non-standard rock mechanics laboratory experiments are being applied in order to obtain the mechanical properties of shales that have not been previously studied in Poland. Novel laboratory investigations were carried out to assess the creep parameters and to determine time-dependent viscoplastic deformation of shale samples, which can provide a limiting factor to tectonic stresses and control stress change caused by hydraulic fracturing. The study was supported by grant no.: 13-03-00-501-90-472946 "An integrated geomechanical investigation to enhance gas extraction from the Pomeranian shale formations", funded by the National Centre for Research and Development (NCBiR). References: Ch. Chang M. D

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

    Energy Technology Data Exchange (ETDEWEB)

    None

    1998-01-01

    Infill drilling if wells on a uniform spacing without regard to reservoir performance and characterization foes not optimize reservoir development because it fails to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, and carbonate reservoirs in particular. New and emerging technologies, such as geostatistical modeling, rigorous decline curve analysis, reservoir rock typing, and special core analysis can be used to develop a 3-D simulation model for prediction of infill locations.

  4. 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.

  5. Prediction of reservoir brine properties using radial basis function (RBF neural network

    Directory of Open Access Journals (Sweden)

    Afshin Tatar

    2015-12-01

    Full Text Available Aquifers, which play a prominent role as an effective tool to recover hydrocarbon from reservoirs, assist the production of hydrocarbon in various ways. In so-called water flooding methods, the pressure of the reservoir is intensified by the injection of water into the formation, increasing the capacity of the reservoir to allow for more hydrocarbon extraction. Some studies have indicated that oil recovery can be increased by modifying the salinity of the injected brine in water flooding methods. Furthermore, various characteristics of brines are required for different calculations used within the petroleum industry. Consequently, it is of great significance to acquire the exact information about PVT properties of brine extracted from reservoirs. The properties of brine that are of great importance are density, enthalpy, and vapor pressure. In this study, radial basis function neural networks assisted with genetic algorithm were utilized to predict the mentioned properties. The root mean squared error of 0.270810, 0.455726, and 1.264687 were obtained for reservoir brine density, enthalpy, and vapor pressure, respectively. The predicted values obtained by the proposed models were in great agreement with experimental values. In addition, a comparison between the proposed model in this study and a previously proposed model revealed the superiority of the proposed GA-RBF model.

  6. 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

  7. Permeability Prediction for Nahr-Umr Reservoir / Subba field by Using FZI Method

    Directory of Open Access Journals (Sweden)

    Sameera M. Hamd- Allah

    2016-09-01

    Full Text Available The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important due to its direct relation to the porosity and permeability. In this study permeability has been predicated by using the flow zone indicator methods. This method attempts to identify the flow zone indicator in un-cored wells using log records. Once the flow zone indicator is calculated from the core data, a relationship between this FZI value and the well logs can be obtained. Three relationships have been found for Nahr-Umr reservoir/Subba field by FZI method. By plotting the permeability of the core versus the permeability that is predicted by FZI method the parameter R2 was found (0.905 which is very good for predict the permeability.

  8. 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  

  9. 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.

  10. 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.

  11. 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

  12. A New Model to Predict Productivity of Multiple-Fractured Horizontal Well in Naturally Fractured Reservoirs

    Directory of Open Access Journals (Sweden)

    Junchao Wang

    2015-01-01

    Full Text Available In order to predict productivity of multiple-fractured horizontal well in fractured reservoir, flow models of reservoir and hydraulic fractures based on the volumetric source idealization are developed. The models are solved by utilizing Laplace transformation and orthogonal transformation, and flow rate of the well is calculated by coupling the two models. Compared to traditional point source functions, volumetric source function has many advantages in properties of function and programming calculation. The productivity predicting model is verified via an analytical ternary-porosity model. Moreover, a practical example of fractured horizontal well is studied to analyze the productivity and its influent factors. The result shows that flow rate of each fracture is different and inner fracture contributes least to productivity. Meanwhile, there are optimizing ranges for number, length, and conductivity of hydraulic fractures. In low-permeability reservoir, increasing surface area in contact with reservoir by increasing number and length of hydraulic fractures is the most effective method to improve the productivity.

  13. 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)

  14. 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.

  15. 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

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. Laser line scan performance prediction

    Science.gov (United States)

    Mahoney, Kevin L.; Schofield, Oscar; Kerfoot, John; Giddings, Tom; Shirron, Joe; Twardowski, Mike

    2007-09-01

    The effectiveness of sensors that use optical measurements for the laser detection and identification of subsurface mines is directly related to water clarity. The primary objective of the work presented here was to use the optical data collected by UUV (Slocum Glider) surveys of an operational areas to estimate the performance of an electro-optical identification (EOID) Laser Line Scan (LLS) system during RIMPAC 06, an international naval exercise off the coast of Hawaii. Measurements of optical backscattering and beam attenuation were made with a Wet Labs, Inc. Scattering Absorption Meter (SAM), mounted on a Rutgers University/Webb Research Slocum glider. The optical data universally indicated extremely clear water in the operational area, except very close to shore. The beam-c values from the SAM sensor were integrated to three attenuation lengths to provide an estimate of how well the LLS would perform in detecting and identifying mines in the operational areas. Additionally, the processed in situ optical data served as near-real-time input to the Electro-Optic Detection Simulator, ver. 3 (EODES-3; Metron, Inc.) model for EOID performance prediction. Both methods of predicting LLS performance suggested a high probability of detection and probability of identification. These predictions were validated by the actual performance of the LLS as the EOID system yielded imagery from which reliable mine identification could be made. Future plans include repeating this work in more optically challenging water types to demonstrate the utility of pre-mission UUV surveys of operational areas as a tactical decision aid for planning EOID missions.

  1. Risk Based Reservoir Operations Using Ensemble Streamflow Predictions for Lake Mendocino in Mendocino County, California

    Science.gov (United States)

    Delaney, C.; Mendoza, J.; Whitin, B.; Hartman, R. K.

    2017-12-01

    Ensemble Forecast Operations (EFO) is a risk based approach of reservoir flood operations that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, each member of an ESP is individually modeled to forecast system conditions and calculate risk of reaching critical operational thresholds. Reservoir release decisions are computed which seek to manage forecasted risk to established risk tolerance levels. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC, which approximates flow forecasts for 61 ensemble members for a 15-day horizon. Model simulation results of the EFO alternative demonstrate a 36% increase in median end of water year (September 30) storage levels over existing operations. Additionally, model results show no increase in occurrence of flows above flood stage for points downstream of Lake Mendocino. This investigation demonstrates that the EFO alternative may be a viable approach for managing Lake Mendocino for multiple purposes (water supply, flood mitigation, ecosystems) and warrants further investigation through additional modeling and analysis.

  2. 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.

  3. Multi-Objective History Matching with a Proxy Model for the Characterization of Production Performances at the Shale Gas Reservoir

    Directory of Open Access Journals (Sweden)

    Jaejun Kim

    2017-04-01

    Full Text Available This paper presents a fast, reliable multi-objective history-matching method based on proxy modeling to forecast the production performances of shale gas reservoirs for which all available post-hydraulic-fracturing production data, i.e., the daily gas rate and cumulative-production volume until the given date, are honored. The developed workflow consists of distance-based generalized sensitivity analysis (DGSA to determine the spatiotemporal-parameter significance, fast marching method (FMM as a proxy model, and a multi-objective evolutionary algorithm to integrate the dynamic data. The model validation confirms that the FMM is a sound surrogate model working within an error of approximately 2% for the estimated ultimate recovery (EUR, and it is 11 times faster than a full-reservoir simulation. The predictive accuracy on future production after matching 1.5-year production histories is assessed to examine the applicability of the proposed method. The DGSA determines the effective parameters with respect to the gas rate and the cumulative volume, including fracture permeability, fracture half-length, enhanced permeability in the stimulated reservoir volume, and average post-fracturing porosity. A comparison of the prediction accuracy for single-objective optimization shows that the proposed method accurately estimates the recoverable volume as well as the production profiles to within an error of 0.5%, while the single-objective consideration reveals the scale-dependency problem with lesser accuracy. The results of this study are useful to overcome the time-consuming effort of using a multi-objective evolutionary algorithm and full-scale reservoir simulation as well as to conduct a more-realistic prediction of the shale gas reserves and the corresponding production performances.

  4. Model design for predicting extreme precipitation event impacts on water quality in a water supply reservoir

    Science.gov (United States)

    Hagemann, M.; Jeznach, L. C.; Park, M. H.; Tobiason, J. E.

    2016-12-01

    Extreme precipitation events such as tropical storms and hurricanes are by their nature rare, yet have disproportionate and adverse effects on surface water quality. In the context of drinking water reservoirs, common concerns of such events include increased erosion and sediment transport and influx of natural organic matter and nutrients. As part of an effort to model the effects of an extreme precipitation event on water quality at the reservoir intake of a major municipal water system, this study sought to estimate extreme-event watershed responses including streamflow and exports of nutrients and organic matter for use as inputs to a 2-D hydrodynamic and water quality reservoir model. Since extreme-event watershed exports are highly uncertain, we characterized and propagated predictive uncertainty using a quasi-Monte Carlo approach to generate reservoir model inputs. Three storm precipitation depths—corresponding to recurrence intervals of 5, 50, and 100 years—were converted to streamflow in each of 9 tributaries by volumetrically scaling 2 storm hydrographs from the historical record. Rating-curve models for concentratoin, calibrated using 10 years of data for each of 5 constituents, were then used to estimate the parameters of a multivariate lognormal probability model of constituent concentrations, conditional on each scenario's storm date and streamflow. A quasi-random Halton sequence (n = 100) was drawn from the conditional distribution for each event scenario, and used to generate input files to a calibrated CE-QUAL-W2 reservoir model. The resulting simulated concentrations at the reservoir's drinking water intake constitute a low-discrepancy sample from the estimated uncertainty space of extreme-event source water-quality. Limiting factors to the suitability of this approach include poorly constrained relationships between hydrology and constituent concentrations, a high-dimensional space from which to generate inputs, and relatively long run

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. A method for improving predictions of bed-load discharges to reservoirs

    Science.gov (United States)

    Lopes, V.L.; Osterkamp, W.R.; Bravo-Espinosa, M.

    2007-01-01

    Effective management options for mitigating the loss of reservoir water storage capacity to sedimentation depend on improved predictions of bed-load discharges into the reservoirs. Most predictions of bed-load discharges, however, are based on the assumption that the rates of bed-load sediment availability equal the transport capacity of the flow, ignoring the spatio-temporal variability of the sediment supply. This paper develops a semiquantitative method to characterize bed-load sediment transport in alluvial channels, assuming a channel reach is non-supply limited when the bed-load discharge of a given sediment particle-size class is functionally related to the energy that is available to transport that fraction of the total bed-load. The method was applied to 22 alluvial stream channels in the USA to determine whether a channel reach had a supply-limited or non-supply-limited bed-load transport regime. The non-supply-limited transport regime was further subdivided into two groups on the basis of statistical tests. The results indicated the pattern of bed-load sediment transport in alluvial channels depends on the complete spectrum of sediment particle sizes available for transport rather than individual particle-size fractions represented by one characteristic particle size. The application of the method developed in this paper should assist reservoir managers in selecting bed-load sediment transport equations to improve predictions of bed-load discharge in alluvial streams, thereby significantly increasing the efficiency of management options for maintaining the storage capacity of waterbodies. ?? 2007 Blackwell Publishing Asia Pty Ltd.

  11. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, M.J.; Orr, F.M. Jr.

    2001-03-26

    This report was an integrated study of the physics and chemistry affecting gas injection, from the pore scale to the field scale, and involved theoretical analysis, laboratory experiments and numerical simulation. Specifically, advances were made on streamline-based simulation, analytical solutions to 1D compositional displacements, and modeling and experimental measures of three-phase flow.

  12. Predicting the natural state of fractured carbonate reservoirs: An Andector Field, West Texas test of a 3-D RTM simulator

    Energy Technology Data Exchange (ETDEWEB)

    Tuncay, K.; Romer, S.; Ortoleva, P. [Indiana Univ., Bloomington, IN (United States); Hoak, T. [Kestrel Geoscience, Littleton, CO (United States); Sundberg, K. [Phillips Petroleum Co., Bartlesville, OK (United States)

    1998-12-31

    The power of the reaction, transport, mechanical (RTM) modeling approach is that it directly uses the laws of geochemistry and geophysics to extrapolate fracture and other characteristics from the borehole or surface to the reservoir interior. The objectives of this facet of the project were to refine and test the viability of the basin/reservoir forward modeling approach to address fractured reservoir in E and P problems. The study attempts to resolve the following issues: role of fracturing and timing on present day location and characteristics; clarifying the roles and interplay of flexure dynamics, changing rock rheological properties, fluid pressuring and tectonic/thermal histories on present day reservoir location and characteristics; and test the integrated RTM modeling/geological data approach on a carbonate reservoir. Sedimentary, thermal and tectonic data from Andector Field, West Texas, were used as input to the RTM basin/reservoir simulator to predict its preproduction state. The results were compared with data from producing reservoirs to test the RTM modeling approach. The effects of production on the state of the field are discussed in a companion report. The authors draw the following conclusions: RTM modeling is an important new tool in fractured reservoir E and P analysis; the strong coupling of RTM processes and the geometric and tensorial complexity of fluid flow and stresses require the type of fully coupled, 3-D RTM model for fracture analysis as pioneered in this project; flexure analysis cannot predict key aspects of fractured reservoir location and characteristics; fracture history over the lifetime of a basin is required to understand the timing of petroleum expulsion and migration and the retention properties of putative reservoirs.

  13. 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.

  14. Prediction of Reservoir Sediment Quality Based on Erosion Processes in Watershed Using Mathematical Modelling

    Directory of Open Access Journals (Sweden)

    Natalia Junakova

    2017-12-01

    Full Text Available Soil erosion, as a significant contributor to nonpoint-source pollution, is ranked top of sediment sources, pollutants attached to sediment, and pollutants in the solution in surface water. This paper is focused on the design of mathematical model intended to predict the total content of nitrogen (N, phosphorus (P, and potassium (K in bottom sediments in small water reservoirs depending on water erosion processes, together with its application and validation in small agricultural watershed of the Tisovec River, Slovakia. The designed model takes into account the calculation of total N, P, and K content adsorbed on detached and transported soil particles, which consists of supplementing the soil loss calculation with a determination of the average nutrient content in topsoils. The dissolved forms of these elements are neglected in this model. Validation of the model was carried out by statistical assessment of calculated concentrations and measured concentrations in Kľušov, a small water reservoir (Slovakia, using the t-test and F-test, at a 0.05 significance level. Calculated concentrations of total N, P, and K in reservoir sediments were in the range from 0.188 to 0.236 for total N, from 0.065 to 0.078 for total P, and from 1.94 to 2.47 for total K. Measured nutrient concentrations in composite sediment samples ranged from 0.16 to 0.26% for total N, from 0.049 to 0.113% for total P, and from 1.71 to 2.42% for total K. The statistical assessment indicates the applicability of the model in predicting the reservoir’s sediment quality detached through erosion processes in the catchment.

  15. 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.

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

    Science.gov (United States)

    Dolfing, Jan; Hubert, Casey R. J.

    2017-01-01

    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. PMID:29312252

  17. 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

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

    DEFF Research Database (Denmark)

    Zhen Wu, Bi Yun

    dependence of Pitzer parameters for NaCl, Na2SO4 and BaCl2 were derived from published osmotic coefficient data (PhD Study 2). Furthermore, barite solubility was determined experimentally at 90 °C and pressures of 150 and 250 bar. Comparison of barite solubilities calculated with the Pitzer model...... of this research was to develop a model, based on thermodynamics and kinetics, for predicting barite precipitation rates in saline waters at the pressures and temperatures of oil bearing reservoirs, using the geochemical modelling code PHREEQC. This task is complicated by the conditions where traditional methods...... to 90 C at 1 bar of pressure. Resulting thermodynamic and kinetic parameters were combined and coupled with PHREEQC to predict precipitation scaling rates in three oil production wells, where barite has been observed. Average linear growth rates of 3, 2.5 and 2 mm of barite per year were estimated...

  19. 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.

  20. Predicting Performance Ratings Using Motivational Antecedents

    National Research Council Canada - National Science Library

    Zazania, Michelle

    1998-01-01

    .... LISREL8 was used to test a path model predicting performance ratings. Results showed observer ratings of effort and self-reported task sell-efficacy played a role in predicting ratings of task-specific performance...

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. The optimized log interpretation method and sweet-spot prediction of gas-bearing shale reservoirs

    Science.gov (United States)

    Tan, Maojin; Bai, Ze; Xu, Jingjing

    2017-04-01

    Shale gas is one of the most important unconventional oil and gas resources, and its lithology and reservoir type are both different from conventional reservoirs [1,2]. "Where are shale reservoirs" "How to determine the hydrocarbon potential" "How to evaluate the reservoir quality", these are some key problems in front of geophysicists. These are sweet spots prediction and quantitative evaluation. As we known, sweet spots of organic shale include geological sweet spot and engineering sweet spot. Geophysical well logging can provide a lot of in-site formation information along the borehole, and all parameters describing the sweet spots of organic shale are attained by geophysical log interpretation[2]. Based on geological and petrophysical characteristics of gas shale, the log response characteristics of gas shales are summarized. Geological sweet spot includes hydrocarbon potential, porosity, fracture, water saturation and total gas content, which can be calculated by using wireline logs[3]. Firstly, the based-logging hydrocarbon potential evaluation is carried out, and the RBF neural network method is developed to estimate the total organic carbon content (TOC), which was proved more effective and suitable than empirical formula and ΔlogR methods [4]. Next, the optimized log interpretation is achieved by using model-searching, and the mineral concentrations of kerogen, clay, feldspar and pyrite and porosity are calculated. On the other hand, engineering sweet spot of shale refers to the rock physical properties and rock mechanism parameters. Some elastic properties including volume module, shear modulus and Poisson's ratio are correspondingly determined from log interpretation, and the brittleness index (BI), effective stress and pore pressure are also estimated. BI is one of the most important engineering sweet spot parameters. A large number of instances show that the summarized log responses can accurately identify the gas-bearing shale, and the proposed RBF

  8. 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

  9. 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...

  10. 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.

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

    Science.gov (United States)

    Soundharajan, B.; Adeloye, A. J.; Remesan, R.

    2015-06-01

    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.

  12. 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 i...

  13. Global prediction of continuous hydrocarbon accumulations in self-sourced reservoirs

    Science.gov (United States)

    Eoff, Jennifer D.

    2012-01-01

    This report was first presented as an abstract in poster format at the American Association of Petroleum Geologists (AAPG) 2012 Annual Convention and Exhibition, April 22-25, Long Beach, Calif., as Search and Discovery Article no. 90142. Shale resource plays occur in predictable tectonic settings within similar orders of magnitude of eustatic events. A conceptual model for predicting the presence of resource-quality shales is essential for evaluating components of continuous petroleum systems. Basin geometry often distinguishes self-sourced resource plays from conventional plays. Intracratonic or intrashelf foreland basins at active margins are the predominant depositional settings among those explored for the development of self-sourced continuous accumulations, whereas source rocks associated with conventional accumulations typically were deposited in rifted passive margin settings (or other cratonic environments). Generally, the former are associated with the assembly of supercontinents, and the latter often resulted during or subsequent to the breakup of landmasses. Spreading rates, climate, and eustasy are influenced by these global tectonic events, such that deposition of self-sourced reservoirs occurred during periods characterized by rapid plate reconfiguration, predominantly greenhouse climate conditions, and in areas adjacent to extensive carbonate sedimentation. Combined tectonic histories, eustatic curves, and paleogeographic reconstructions may be useful in global predictions of organic-rich shale accumulations suitable for continuous resource development. Accumulation of marine organic material is attributed to upwellings that enhance productivity and oxygen-minimum bottom waters that prevent destruction of organic matter. The accumulation of potential self-sourced resources can be attributed to slow sedimentation rates in rapidly subsiding (incipient, flexural) foreland basins, while flooding of adjacent carbonate platforms and other cratonic highs

  14. 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...

  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. Prediction of biochemical oxygen demand at the upstream catchment of a reservoir using adaptive neuro fuzzy inference system.

    Science.gov (United States)

    Chiu, Yung-Chia; Chiang, Chih-Wei; Lee, Tsung-Yu

    2017-10-01

    The aim of this study is to examine the potential of adaptive neuro fuzzy inference system (ANFIS) to estimate biochemical oxygen demand (BOD). To illustrate the applicability of ANFIS method, the upstream catchment of Feitsui Reservoir in Taiwan is chosen as the case study area. The appropriate input variables used to develop the ANFIS models are determined based on the t-test. The results obtained by ANFIS are compared with those by multiple linear regression (MLR) and artificial neural networks (ANNs). Simulated results show that the identified ANFIS model is superior to the traditional MLR and nonlinear ANNs models in terms of the performance evaluated by the Pearson coefficient of correlation, the root mean square error, the mean absolute percentage, and the mean absolute error. These results indicate that ANFIS models are more suitable than ANNs or MLR models to predict the nonlinear relationship within the variables caused by the complexity of aquatic systems and to produce the best fit of the measured BOD concentrations. ANFIS can be seen as a powerful predictive alternative to traditional water quality modeling techniques and extended to other areas to improve the understanding of river pollution trends.

  17. Predicting performance : relative importance of students' background and past performance

    NARCIS (Netherlands)

    Stegers-Jager, Karen M.; Themmen, Axel P. N.; Cohen-Schotanus, Janke; Steyerberg, Ewout W.

    ContextDespite evidence for the predictive value of both pre-admission characteristics and past performance at medical school, their relative contribution to predicting medical school performance has not been thoroughly investigated. ObjectivesThis study was designed to determine the relative

  18. 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.

  19. Measuring and predicting reservoir heterogeneity in complex deposystems: The fluvial-deltaic Big Injun sandstone in West Virginia

    Energy Technology Data Exchange (ETDEWEB)

    Patchen, D.G.; Hohn, M.E.; Aminian, K.; Donaldson, A.; Shumaker, R.; Wilson, T.

    1993-04-01

    The purpose of this research is to develop techniques to measure and predict heterogeneities in oil reservoirs that are the products of complex deposystems. The unit chosen for study is the Lower Mississippian Big Injun sandstone, a prolific oil producer (nearly 60 fields) in West Virginia. This research effort has been designed and is being implemented as an integrated effort involving stratigraphy, structural geology, petrology, seismic study, petroleum engineering, modeling and geostatistics. Sandstone bodies are being mapped within their regional depositional systems, and then sandstone bodies are being classified in a scheme of relative heterogeneity to determine heterogeneity across depositional systems. Facies changes are being mapped within given reservoirs, and the environments of deposition responsible for each facies are being interpreted to predict the inherent relative heterogeneity of each facies. Structural variations will be correlated both with production, where the availability of production data will permit, and with variations in geologic and engineering parameters that affect production. A reliable seismic model of the Big Injun reservoirs in Granny Creek field is being developed to help interpret physical heterogeneity in that field. Pore types are being described and related to permeability, fluid flow and diagenesis, and petrographic data are being integrated with facies and depositional environments to develop a technique to use diagenesis as a predictive tool in future reservoir development. Another objective in the Big Injun study is to determine the effect of heterogeneity on fluid flow and efficient hydrocarbon recovery in order to improve reservoir management. Graphical methods will be applied to Big Injun production data and new geostatistical methods will be developed to detect regional trends in heterogeneity.

  20. Prediction of mirror performance from laboratory measurements

    International Nuclear Information System (INIS)

    Church, E.L.; Takacs, P.Z.

    1989-01-01

    This paper describes and illustrates a simple method of predicting the imaging performance of synchrotron mirrors from laboratory measurements of their profiles. It discusses the important role of the transverse coherence length of the incident radiation, the fractal-like form of the mirror roughness, mirror characterization, and the use of closed-form expressions for the predicted image intensities

  1. 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...

  2. Lithofacies paleogeography mapping and reservoir prediction in tight sandstone strata: A case study from central Sichuan Basin, China

    Directory of Open Access Journals (Sweden)

    Yuan Zhong

    2017-09-01

    Full Text Available Sand-rich tight sandstone reservoirs are potential areas for oil and gas exploration. However, the high ratio of sandstone thickness to that of the strata in the formation poses many challenges and uncertainties to traditional lithofacies paleogeography mapping. Therefore, the prediction of reservoir sweet spots has remained problematic in the field of petroleum exploration. This study provides new insight into resolving this problem, based on the analyses of depositional characteristics of a typical modern sand-rich formation in a shallow braided river delta of the central Sichuan Basin, China. The varieties of sand-rich strata in the braided river delta environment include primary braided channels, secondary distributary channels and the distribution of sediments is controlled by the successive superposed strata deposited in paleogeomorphic valleys. The primary distributary channels have stronger hydrodynamic forces with higher proportions of coarse sand deposits than the secondary distributary channels. Therefore, lithofacies paleogeography mapping is controlled by the geomorphology, valley locations, and the migration of channels. We reconstructed the paleogeomorphology and valley systems that existed prior to the deposition of the Xujiahe Formation. Following this, rock-electro identification model for coarse skeletal sand bodies was constructed based on coring data. The results suggest that skeletal sand bodies in primary distributary channels occur mainly in the valleys and low-lying areas, whereas secondary distributary channels and fine deposits generally occur in the highland areas. The thickness distribution of skeletal sand bodies and lithofacies paleogeography map indicate a positive correlation in primary distributary channels and reservoir thickness. A significant correlation exists between different sedimentary facies and petrophysical properties. In addition, the degree of reservoir development in different sedimentary facies

  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. 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)

  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. 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

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

    African Journals Online (AJOL)

    cce

    African Journal of Educational Studies in Mathematics and Sciences Vol. 4, 2006. 41. Predicting Students' Performance in the Senior Secondary. Certificate Examinations from Performance in the Junior Secondary. Certificate Examinations in Ondo State, igeria. Adeyemi, T. O.. Department of Educational Foundations and ...

  8. Reconciling longwall gob gas reservoirs and venthole production performances using multiple rate drawdown well test analysis

    Energy Technology Data Exchange (ETDEWEB)

    Karacan, C. Oezgen [National Institute for Occupational Safety and Health (NIOSH), Pittsburgh Research Laboratory, Pittsburgh 15236, PA (United States)

    2009-12-01

    Longwall mining is an underground mining method during which a mechanical shearer progressively mines a large block of coal, called a panel, in an extensive area. During this operation the roof of the coal seam is supported only temporarily with hydraulic supports that protect the workers and the equipment on the coal face. As the coal is extracted, the supports automatically advance and the roof strata cave behind the supports. Caving results in fracturing and relaxation of the overlying strata, which is called ''gob.'' Due its highly fractured nature, gob contains many flow paths for gas migration. Thus, if the overlying strata contain gassy sandstones or sandstone channels, gas shales or thinner coal seams which are not suitable for mining, then the mining-induced changes can cause unexpected or uncontrolled gas migration into the underground workplace. Vertical gob gas ventholes (GGV) are drilled into each longwall panel to capture the methane within the overlying fractured strata before it enters the work environment. Thus, it is important, first to understand the properties of the gas reservoir created by mining disturbances and, second, to optimize the well parameters and placement accordingly. In this paper, the production rate-pressure behaviors of six GGVs drilled over three adjacent panels were analyzed by using conventional multi-rate drawdown analysis techniques. The analyses were performed for infinite acting and pseudo-steady state flow models, which may be applicable during panel mining (DM) and after mining (AM) production periods of GGVs. These phases were analyzed separately since the reservoir properties, due to dynamic subsidence, boundary conditions and gas capacity of the gob reservoir may change between these two stages. The results suggest that conventional well test analysis techniques can be applicable to highly complex gob reservoirs and GGVs to determine parameters such as skin, permeability, radius of investigation

  9. Live Imaging of Micro-Wettability Experiments Performed for Low-Permeability Oil Reservoirs.

    Science.gov (United States)

    Deglint, Hanford J; Clarkson, Christopher R; DeBuhr, Chris; Ghanizadeh, Amin

    2017-06-28

    Low-permeability (unconventional) hydrocarbon reservoirs exhibit a complex nanopore structure and micro (µm) -scale variability in composition which control fluid distribution, displacement and transport processes. Conventional methods for characterizing fluid-rock interaction are however typically performed at a macro (mm) -scale on rock sample surfaces. In this work, innovative methods for the quantification of micro-scale variations in wettability and fluid distribution in a low-permeability oil reservoir was enabled by using an environmental scanning electron microscope. Live imaging of controlled water condensation/evaporation experiments allowed micro-droplet contact angles to be evaluated, while imaging combined with x-ray mapping of cryogenically frozen samples facilitated the evaluation of oil and water micro-droplet contact angles after successive fluid injection. For the first time, live imaging of fluids injected through a micro-injection system has enabled quantification of sessile and dynamic micro-droplet contact angles. Application of these combined methods has revealed dramatic spatial changes in fluid contact angles at the micro-scale, calling into question the applicability of macro-scale observations of fluid-rock interaction.

  10. 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.

  11. PREDICTING PERFORMANCE OF WEB SERVICES USING SMTQA

    OpenAIRE

    Ch Ram Mohan Reddy; D Evangelin Geetha; KG Srinivasa; T V Suresh Kumar; K Rajani Kanth

    2011-01-01

    Web Service is an interface which implements business logic. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In this paper we model web service using Unified Modeling Language, Use Case Diagram, Sequence Diagram. We obtain the Performance metrics by simulating the web services model using a simulation tool Simulation of Multi-Tie...

  12. Early Performance Prediction of Web Services

    OpenAIRE

    Reddy, Ch Ram Mohan; Geetha, D. Evangelin; Srinivasa, K. G.; Kumar, T. V. Suresh; Kanth, K. Rajani

    2012-01-01

    Web Service is an interface which implements business logic. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In this paper we model web service using Unified Modeling Language, Use Case Diagram, Sequence Diagram, Deployment Diagram. We obtain the Performance metrics by simulating the web services model using a simulation tool Simulation of Mult...

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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...... Center. Here, the flood forecast model coupled with the rainfall forecast from RSM has been employed to carry out real-time dynamic control of the Flood Limiting Water Level (FLWL) of TGR in order to improve the hydropower generation without increasing the flood risk. Taking the flood events of the flood...

  18. Volume 4: Characterization of representative reservoirs -- Gulf of Mexico field, U-8 reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Koperna, G.J. Jr.; Johnson, H.R. [BDM Federal, Inc., McLean, VA (United States); Salamy, S.P.; Reeves, T.K. [BDM-Oklahoma, Inc., Bartlesville, OK (United States); Sawyer, W.K. [Mathematical and Computer Services, Inc., Danville, VA (United States); Kimbrell, W.C.; Schenewerk, P.A. [Louisiana State Univ., Baton Rouge, LA (United States). Dept. of Petroleum Engineering

    1998-07-01

    A reservoir study was performed using a publicly available black oil simulator to history match and predict the performance of a Gulf of Mexico reservoir. The first objective of this simulation study was to validate the Black Oil Applied Simulation Tool version three for personal computers (BOAST3-PC) model to ensure the integrity of the simulation runs. Once validation was completed, a field history match for the Gulf of Mexico U-8 oil reservoir was attempted. A verbal agreement was reached with the operator of this reservoir to blindcode the name and location of the reservoir. In return, the operator supplied data and assistance in regards to the technical aspects of the research. On the basis of the best history match, different secondary recovery techniques were simulated as a predictive study for enhancing the reservoir productivity.

  19. 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...

  20. What predicts performance during clinical psychology training?

    Science.gov (United States)

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

    2014-06-01

    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. Longitudinal cross-sectional study using prospective and retrospective data. Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. © 2013 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

  1. Why Do Spatial Abilities Predict Mathematical Performance?

    Science.gov (United States)

    Tosto, Maria Grazia; Hanscombe, Ken B.; Haworth, Claire M. A.; Davis, Oliver S. P.; Petrill, Stephen A.; Dale, Philip S.; Malykh, Sergey; Plomin, Robert; Kovas, Yulia

    2014-01-01

    Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance.…

  2. Predictability of steer performance in the feedlot

    African Journals Online (AJOL)

    ance and overall performance is closely correlated. A further advantage would be if the growth and feed conversion-time curves could be predicted with confidence because feedlot management can then optimize duration of feeding periods to cash in on favourable market conditions. This in turn will require particular and ...

  3. Prediction of aerodynamic performance for MEXICO rotor

    DEFF Research Database (Denmark)

    Hong, Zedong; Yang, Hua; Xu, Haoran

    2013-01-01

    The aerodynamic performance of the MEXICO (Model EXperiments In Controlled cOnditions) rotor at five tunnel wind speeds is predicted by making use of BEM and CFD methods, respectively, using commercial MATLAB and CFD software. Due to the pressure differences on both sides of the blade, the tip-fl...

  4. What predicts performance during clinical psychology training?

    Science.gov (United States)

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

    2014-01-01

    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 range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Results Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Conclusions Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. Practitioner points While referee and selection interview ratings did not predict performance during training, they may be useful in screening out unsuitable candidates at the application stage High school final academic performance

  5. 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.

  6. Prediction of Interfacial Tensions of Reservoir Crude Oil and Gas Condensate Systems

    DEFF Research Database (Denmark)

    Zuo, You-Xiang; Stenby, Erling Halfdan

    1998-01-01

    . Correlations of the model parameters were presented for pseudocomponents. The characterization procedures of Pedersen et al. and the SRK equation of state (EOS) were used to calculate vapor-liquid equilibria (VLE). To the exclusion of the near-critical region, the IFT’s calculated by all the models except...... the CS correlation were in good agreement with the measured IFT data for several crude oil and CO2/oil systems. The SLGT model and the parachor model perform better than the LGT model and the CS correlation. For N 2 volatile oil systems, the performance of the LGT model is better than that of the SLGT...... model and the parachor model. For gas condensate systems, the predictions by use of the SLGT model are in good agreement with the measured IFT data. In the near-critical region, a correlation was proposed for estimations of IFT’s for CO2/oil systems, and satisfactory correlated results were obtained....

  7. 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

  8. 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

  9. What predicts performance in Canadian dental schools?

    Science.gov (United States)

    Smithers, S; Catano, V M; Cunningham, D P

    2004-06-01

    The task of selecting the best dental applicants out of an extremely competitive applicant pool is a problem faced annually by dental faculties. This study examined the validity of both cognitive and noncognitive factors used for selection to Canadian dental schools. Interest in personality measurement and the prediction offered by personality measures has escalated and may be applied to the selection of dental candidates. Therefore, the study also assessed whether the addition of a personality measure would increase the validity of predicting performance beyond that achieved by an interview and the Dental Aptitude Test. Results suggest that an interview may be useful in identifying specific behavioral characteristics deemed important for success in dental training. Consistent with previous research, results show that the Dental Aptitude Test is a good predictor of preclinical academic success, with prediction declining when clinical components of the program are introduced into the criterion. Results from the personality measure indicated that Openness to Experience was significantly related to aspects of clinical education, although, contrary to expectations, this relationship was negative. A facet of Openness, Ideas, together with Positive Emotions, a facet of Extroversion, improved prediction of performance in clinical studies beyond that provided by the Dental Aptitude Test and the Interview. Implications of the findings are discussed, and recommendations regarding the admission process to Canadian dental programs are offered.

  10. Investigating the Performance of the Jason-2/OSTM Radar Altimeter Over Lakes and Reservoirs

    Science.gov (United States)

    Birkett, C. M.; Beckley, B.

    2010-01-01

    Many inland water investigations utilize archival and near-real time radar altimetry data to enable observation of the variation in surface water level. A multi-altimeter approach allows a more global outlook with improved spatial resolution, and combined long-term observations improve statistical analyses. Central to all programs is a performance assessment of each instrument. Here, we focus on data quantity and quality pertaining to the Poseidon-3 radar altimeter onboard the Jason-2/OSTM satellite.Utilizing an interim data set (IGDR), studies show that the new on-board DIODE/median and DIODE/DEM tracking modes are performing well, acquiring and maintaining the majority of lake and reservoir surfaces in varying terrains. The 20-Hz along-track resolution of the data, and particularly the availability of the range output from the ice-retracker algorithm, also improves the number of valid height measurements. Based on test-case lakes and reservoirs, output from the ice-retracker algorithm is also seen to have a clear advantage over the ocean-retracker having better height stability across calm and icy surfaces, a greater ability to gain coastline waters, and less sensitivity to loss of water surface when there is island contamination in the radar echo. Such on-board tracking and postprocessing retracking enables the lake waters to be quickly gained after coastline crossing. Values can range from <0.1 s to 2.5 s, but the majority of measurements are obtained in less than 0.4 s or <2.3 km from the coast. Validation exercises reveal that targets of 150 km2 surface area and 0.8 km width are able to be monitored offering greater potential to acquire lakes in the 100 C300 km2 size-category. Time series of height variations are also found to be accurate to 3 to 33 cm rms depending on target size and the presence of winter ice. These findings are an improvement over the IGDR/GDR results from the predecessor Jason-1 and TOPEX/Poseidon missions and can satisfy the accuracy

  11. Reservoir formation mechanism analysis and deep high-quality reservoir prediction in Yingcheng Formation in Longfengshan area of Songliao Basin, China

    Directory of Open Access Journals (Sweden)

    Yongmei Zhang

    2016-12-01

    Full Text Available Although commercial gas flow was produced in several wells with recent years' exploration of Longfengshan area in Changling fault sag, the formation mechanism and controlling factors for high-quality reservoirs still remained undefined. Here, the Yingcheng tight gas reservoirs of Longfengshan area are used as an example to characterize high-quality reservoir formation mechanism and distribution rules. Based on the thin section, SEM, X-ray diffraction, computed tomography (CT scanning, burial history, constant-rate mercury penetration and physical properties testing, formation mechanism and controlling factors for high-quality reservoirs were analyzed. Results show the following characteristics. First, the reservoir is dominated by chlorite and laumontite cements, and compaction is the most important factor to control reservoir physical properties. According to this, the reservoir can be divided into compacted tight sandstones, chlorite-cemented sandstones and laumontite-cemented sandstones. Second, the high-quality reservoirs are formed due to early extensive laumontite precipitation and the later dissolution of laumontite by organic acid. Meanwhile, it is found that the distribution of cementation and dissolution exhibits some regulations in sedimentary facies, and the distribution is mainly effected and controlled by the lake water and charging of fresh water. Besides, the distribution model of various types of sandstones was established. Studies over diagenesis and sedimentary facies reveal that the high-quality laumontite-cemented sandstones exist in the outside subaqueous fan-delta of the deep sag in Longfengshan area. These findings have been validated by recent exploration wells which obtained high industrial gas flow.

  12. 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.

  13. 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.

  14. 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.

  15. Analysis of Geologic Parameters on the Performance of CO2-Plume Geothermal (CPG) Systems in a Multi-Layered Reservoirs

    Science.gov (United States)

    Garapati, N.; Randolph, J.; Saar, M. O.

    2013-12-01

    CO2-Plume Geothermal (CPG) involves injection of CO2 as a working fluid to extract heat from naturally high permeable sedimentary basins. The injected CO2 forms a large subsurface CO2 plume that absorbs heat from the geothermal reservoir and eventually buoyantly rises to the surface. The heat density of sedimentary basins is typically relatively low.However, this drawback is likely counteracted by the large accessible volume of natural reservoirs compared to artificial, hydrofractured, and thus small-scale, reservoirs. Furthermore, supercritical CO2has a large mobility (inverse kinematic viscosity) and expansibility compared to water resulting in the formation of a strong thermosiphon which eliminates the need for parasitic pumping power requirements and significantly increasing electricity production efficiency. Simultaneously, the life span of the geothermal power plant can be increased by operating the CPG system such that it depletes the geothermal reservoir heat slowly. Because the produced CO2 is reinjected into the ground with the main CO2 sequestration stream coming from a CO2 emitter, all of the CO2 is ultimately geologically sequestered resulting in a CO2 sequestering geothermal power plant with a negative carbon footprint. Conventional geothermal process requires pumping of huge amount of water for the propagation of the fractures in the reservoir, but CPG process eliminates this requirement and conserves water resources. Here, we present results for performance of a CPG system as a function of various geologic properties of multilayered systemsincludingpermeability anisotropy, rock thermal conductivity, geothermal gradient, reservoir depth and initial native brine salinity as well as spacing between the injection and production wells. The model consists of a 50 m thick, radially symmetric grid with a semi-analytic heat exchange and no fluid flow at the top and bottom boundaries and no fluid and heat flow at the lateral boundaries. We design Plackett

  16. 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.

  17. 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

  18. Analysis of the Influencing Factors on the Well Performance in Shale Gas Reservoir

    Directory of Open Access Journals (Sweden)

    Cheng Dai

    2017-01-01

    Full Text Available Due to the ultralow permeability of shale gas reservoirs, stimulating the reservoir formation by using hydraulic fracturing technique and horizontal well is required to create the pathway of gas flow so that the shale gas can be recovered in an economically viable manner. The hydraulic fractured formations can be divided into two regions, stimulated reservoir volume (SRV region and non-SRV region, and the produced shale gas may exist as free gas or adsorbed gas under the initial formation condition. Investigating the recovery factor of different types of shale gas in different region may assist us to make more reasonable development strategies. In this paper, we build a numerical simulation model, which has the ability to take the unique shale gas flow mechanisms into account, to quantitatively describe the gas production characteristics in each region based on the field data collected from a shale gas reservoir in Sichuan Basin in China. The contribution of the free gas and adsorbed gas to the total production is analyzed dynamically through the entire life of the shale gas production by adopting a component subdivision method. The effects of the key reservoir properties, such as shale matrix, secondary natural fracture network, and primary hydraulic fractures, on the recovery factor are also investigated.

  19. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1). Annual report, February 1, 1991--January 31, 1992

    Energy Technology Data Exchange (ETDEWEB)

    Watney, W.L.

    1992-08-01

    Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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)

  5. A Comparative Study of Reservoir Computing for Temporal Signal Processing

    OpenAIRE

    Goudarzi, Alireza; Banda, Peter; Lakin, Matthew R.; Teuscher, Christof; Stefanovic, Darko

    2014-01-01

    Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir's state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who study the task-solving performance and computational power of RC. In addition, in contrast to tradit...

  6. 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

  7. Using underground gas storage to replace the swing capacity of the giant natural gas field of Groningen in the Netherlands. A reservoir performance feasibility study.

    Science.gov (United States)

    Juez-Larre, Joaquim; Remmelts, Gijs; Breunese, Jaap; Van Gessel, Serge; Leeuwenburgh, Olwijn

    2017-04-01

    In this study we probe the ultimate potential Underground Gas Storage (UGS) capacity of the Netherlands by carrying out a detailed feasibility study on inflow performances of all available onshore natural gas reservoirs. The Netherlands is one of the largest natural gas producers in Western Europe. The current decline of its national production and looming production restrictions on its largest field of Groningen -owing to its induced seismicity- have recently made necessary to upgrade the two largest UGS of Norg and Grijpskerk. The joined working volume of these two UGS is expected to replace the swing capacity of the Groningen field to continue guaranteeing the security of supply of low calorific natural gas. The question is whether the current UGS configuration will provide the expected working storage capacity unrestricted by issues on reservoir performances and/or induced seismicity. This matter will be of paramount importance in the near future when production restrictions and/or the advance state of depletion of the Groningen field will turn the Netherlands into a net importer of high calorific natural gas. By then, the question will be whether the current UGS will still be economically attractive to continue operating, or if additional/alternative types of UGS will be needed?. Hence the characterization and ranking of the best potential reservoirs available today is of paramount importance for future UGS developments. We built an in-house automated module based on the application of the traditional inflow performance relationship analysis to screen the performances of 156 natural gas reservoirs in onshore Netherlands. Results enable identifying the 72 best candidates with an ultimate total working volume capacity of 122±30 billion Sm3. A detailed sensitivity analysis shows the impact of variations in the reservoir properties or wellbore/tubing configurations on withdrawal performances and storage capacity. We validate our predictions by comparing them to

  8. 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...

  9. Applying SWAT to predict ortho-phosphate loads and trophic status in four reservoirs in the upper Olifants catchment, South Africa

    CSIR Research Space (South Africa)

    Dabrowski, James M

    2014-07-01

    Full Text Available source of bioavailable orthophosphate (OP) in the catchment. The Soil Water Assessment Tool (SWAT) was used to identify important sources of OP loading in the catchment and to predict changes in the trophic status of four reservoirs associated with three...

  10. Changes in Memory Prediction Accuracy: Age and Performance Effects

    Science.gov (United States)

    Pearman, Ann; Trujillo, Amanda

    2013-01-01

    Memory performance predictions are subjective estimates of possible memory task performance. The purpose of this study was to examine possible factors related to changes in word list performance predictions made by younger and older adults. Factors included memory self-efficacy, actual performance, and perceptions of performance. The current study…

  11. 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.

  12. From Hydroclimatic Prediction to Negotiated and Risk Managed Water Allocation and Reservoir Operation (Invited)

    Science.gov (United States)

    Lall, U.

    2013-12-01

    The availability of long lead climate forecasts that can in turn inform streamflow, agricultural, ecological and municipal/industrial and energy demands provides an opportunity for innovations in water resources management that go beyond the current practices and paradigms. In a practical setting, managers seek to meet registered demands as well as they can. Pricing mechanisms to manage demand are rarely invoked. Drought restrictions and operations are implemented as needed, and pressures from special interest groups are sometimes accommodated through a variety of processes. In the academic literature, there is a notion that demand curves for different sectors could be established and used for "optimal management". However, the few attempts to implement such ideas have invariably failed as elicitation of demand elasticity and socio-political factors is imperfect at best. In this talk, I will focus on what is worth predicting and for whom and how operational risks for the water system can be securitized while providing a platform for priced and negotiated allocation of the resources in the presence of imperfect forecasts. The possibility of a national or regional market for water contracts as part of the framework is explored, and its potential benefits and pitfalls identified.

  13. Evaporation suppression from reservoirs using floating covers: Lab scale wind-tunnel observations and mechanistic model predictions

    Science.gov (United States)

    Or, Dani; Lehmann, Peter; Aminzadeh, Milad; Sommer, Martina; Wey, Hannah; Krentscher, Christiane; Wunderli, Hans; Breitenstein, Daniel

    2017-04-01

    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. We report a systematic experimental evaluation of different cover types and external drivers (radiation, wind, wind plus 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.

  14. Some practical aspects of reservoir management

    Energy Technology Data Exchange (ETDEWEB)

    Fowler, M.L.; Young, M.A.; Cole, E.L.; Madden, M.P. [BDM-Oklahoma, Bartlesville, OK (United States)

    1996-09-01

    The practical essence of reservoir management is the optimal application of available resources-people, equipment, technology, and money to maximize profitability and recovery. Success must include knowledge and consideration of (1) the reservoir system, (2) the technologies available, and (3) the reservoir management business environment. Two Reservoir Management Demonstration projects (one in a small, newly-discovered field and one in a large, mature water-flood) implemented by the Department of Energy through BDM-Oklahoma illustrate the diversity of situations suited for reservoir management efforts. Project teams made up of experienced engineers, geoscientists, and other professionals arrived at an overall reservoir management strategy for each field. in 1993, Belden & Blake Corporation discovered a regionally significant oil reservoir (East Randolph Field) in the Cambrian Rose Run formation in Portage County, Ohio. Project objectives are to improve field operational economics and optimize oil recovery. The team focused on characterizing the reservoir geology and analyzing primary production and reservoir data to develop simulation models. Historical performance was simulated and predictions were made to assess infill drilling, water flooding, and gas repressurization. The Citronelle Field, discovered in 1955 in Mobile County, Alabama, has produced 160 million barrels from fluvial sandstones of the Cretaceous Rodessa formation. Project objectives are to address improving recovery through waterflood optimization and problems related to drilling, recompletions, production operations, and regulatory and environmental issues. Initial efforts focused on defining specific problems and on defining a geographic area within the field where solutions might best be pursued. Geologic and reservoir models were used to evaluate past performance and to investigate improved recovery operations.

  15. 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...

  16. 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

  17. 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.

  18. 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.

  19. Increasing the predictive power of geostatistical reservoir models by integration of geological constraints from stratigraphic forward modeling

    NARCIS (Netherlands)

    Sacchi, Q.; Borello, E.S.; Weltje, G.J.; Dalman, R.

    2016-01-01

    Current static reservoir models are created by quantitative integration of interpreted well and seismic data through geostatistical tools. In these models, equiprobable realizations of structural settings and property distributions can be generated by stochastic simulation techniques. The

  20. 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

  1. Tailoring dam structures to water quality predictions in new reservoir projects: assisting decision-making using numerical modeling.

    Science.gov (United States)

    Marcé, Rafael; Moreno-Ostos, Enrique; García-Barcina, José Ma; Armengol, Joan

    2010-06-01

    Selection of reservoir location, the floodable basin forest handling, and the design of dam structures devoted to water supply (e.g. water outlets) constitute relevant features which strongly determine water quality and frequently demand management strategies to be adopted. Although these crucial aspects should be carefully examined during dam design before construction, currently the development of ad hoc limnological studies tailoring dam location and dam structures to the water quality characteristics expected in the future reservoir is not typical practice. In this study, we use numerical simulation to assist on the design of a new dam project in Spain with the aim of maximizing the quality of the water supplied by the future reservoir. First, we ran a well-known coupled hydrodynamic and biogeochemical dynamic numerical model (DYRESM-CAEDYM) to simulate the potential development of anoxic layers in the future reservoir. Then, we generated several scenarios corresponding to different potential hydraulic conditions and outlet configurations. Second, we built a simplified numerical model to simulate the development of the hypolimnetic oxygen content during the maturation stage after the first reservoir filling, taking into consideration the degradation of the terrestrial organic matter flooded and the adoption of different forest handling scenarios. Results are discussed in terms of reservoir design and water quality management. The combination of hypolimnetic withdrawal from two deep outlets and the removal of all the valuable terrestrial vegetal biomass before flooding resulted in the best water quality scenario. (c) 2010 Elsevier Ltd. All rights reserved.

  2. Predicting thermal performance in occupied dwellings

    Energy Technology Data Exchange (ETDEWEB)

    Kruger, E.; Givoni, B. [Energy Engineering Section, Department of Mechanical Engineering, Technical University of Denmark, Lyngby (Denmark)

    2004-07-01

    The main purpose of formulating methodologies for building systems' evaluation in low-cost housing is to find an effective solution for the huge Brazilian housing deficit of approximately five million housing units, mainly due to an accelerated population growth in urban centers. Low-cost housing programs are usually implemented in a broad sense, with no regard to local specific conditions. Thus, building systems of quite similar characteristics are employed in places with different climatic conditions, which leads to low-quality houses that do not respond to the users' needs. In this paper, the results of the application of formulas to predict daily indoor temperatures in three monitored low-cost houses in Curitiba, Brazil, are presented. The houses were occupied by families having neither cooling nor heating devices and are built of different building materials with different thermal properties. The monitoring of the houses took place both in winter and in summer. Measured data were also compared with simulated data. In this case, the French software COMFIE was used. Finally, the results of the thermal simulations were compared with those of predictive formulas developed by Givoni. (author)

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

    OpenAIRE

    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 bridging program. Many Dutch universities set up bridging programs that aim to prepare students with non-university degrees in the Netherlands for Master’s programs at the university level. Some univ...

  4. 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

  5. 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.

  6. 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)

  7. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex I). Twelfth quarterly technical progress report, October 1, 1992--December 31, 1992

    Energy Technology Data Exchange (ETDEWEB)

    Watney, W.L.

    1992-12-31

    The objectives of this research are to: (1) assist producers in locating and producing petroleum not currently being produced because of technological problems or the inability to identify details of reservoir compartmentalization, (2) to decrease risk in field development, and (3) accelerate the retrieval and analysis of baseline geoscience information for initial reservoir description. The interdisciplinary data sought in this research will be used to resolve specific problems in correlation of strata and to establish the mechanisms responsible for the Upper Pennsylvanian stratigraphic architecture in the Midcontinent. The data will better constrain ancillary problems related to the validation of depositional sequence and subsequence correlation, subsidence patterns, sedimentation rates, sea-level changes, and the relationship of sedimentary sequences to basement terrains. The geoscientific information, including data from field studies, surface and near-surface reservoir analogues, and regional data base development, will also be used for development of geologic computer process-based simulation models tailored to specific depositional sequences for use in improving prediction of reservoir characteristics.

  8. Accurate torque-speed performance prediction for brushless dc motors

    Science.gov (United States)

    Gipper, Patrick D.

    Desirable characteristics of the brushless dc motor (BLDCM) have resulted in their application for electrohydrostatic (EH) and electromechanical (EM) actuation systems. But to effectively apply the BLDCM requires accurate prediction of performance. The minimum necessary performance characteristics are motor torque versus speed, peak and average supply current and efficiency. BLDCM nonlinear simulation software specifically adapted for torque-speed prediction is presented. The capability of the software to quickly and accurately predict performance has been verified on fractional to integral HP motor sizes, and is presented. Additionally, the capability of torque-speed prediction with commutation angle advance is demonstrated.

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

    African Journals Online (AJOL)

    cce

    the use of z- test, correlation analysis and multiple regression. The findings revealed .... The choice of the subjects was in accordance with ... Adeyemi, T. O.. 44. Table 2: Credit Performance in SSC Examinations in Sampled Schools. Years. English language. Mathematics Physics. Chemistry. Biology. %. %. %. %. %. 2000. 8.

  10. 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

  11. 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,…

  12. 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

  13. Alpine Skiing Recommendation Tool and Performance Prediction

    Directory of Open Access Journals (Sweden)

    Camille Brousseau

    2018-02-01

    Full Text Available Selecting appropriate skis remains a difficult task for many customers due to the lack of information provided on the bending and torsional stiffnesses of these products. This work investigates how these mechanical properties influence the on-snow ski performance and how an individual skier profile is related to its preferred mechanical properties. To do so, twelve skis were manufactured to exhibit large variations in stiffnesses. Twenty-three skiers provided on-snow feedback and skier profiles through a questionnaire. Simple and multivariable linear correlation analyses were carried out between the skier profile data, their evaluations of the skis and the stiffnesses of the skis. Strong relationships were found between the properties of the skis and some performance criteria, and between the profile of the skiers and the properties of their favourite skis. With further testing, these relationships could be used to design personalized recommendation tools or to guide the design of custom skis.

  14. 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

  15. 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.

  16. Performance predictions improve prospective memory and influence retrieval experience.

    Science.gov (United States)

    Meier, Beat; von Wartburg, Philipp; Matter, Sibylle; Rothen, Nicolas; Reber, Rolf

    2011-03-01

    In retrospective memory, performance predictions have been found to enhance performance on subsequent memory tests. In prospective memory, the influence of metacognitive judgments on performance has not been investigated systematically. In the present study, 140 undergraduate students performed a complex short-term memory task that included a prospective memory task. Half of them gave performance predictions after the prospective memory task instructions. In addition, the specificity of the prospective memory task was manipulated by instructing participants either to perform an action when a word that belongs to the category of musical instruments was presented or to respond when the word "trumpet" was presented. The results showed that performance predictions enhanced performance, but only for the categorical task. Additional analyses of retrieval experience showed that performance predictions lead to an increase in search experiences while cue specificity was accompanied by an increase in pop up experiences. The results indicate that performance predictions can improve prospective performance and thus may be a valuable strategy for assisting prospective memory. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

  17. Application of Integrated Reservoir Management and Reservoir Characterization to Optimize Infill Drillings. Annual technical progress report, June 13, 1996 to June 12, 1998

    Energy Technology Data Exchange (ETDEWEB)

    Nevans, Jerry W.; Blasingame, Tom; Doublet, Louis; Kelkar, Mohan; Freeman, George; Callard, Jeff; Moore, David; Davies, David; Vessell, Richard; Pregger, Brian; Dixon, Bill

    1999-04-27

    Infill drilling of wells on a uniform spacing, without regard to reservoir performance and characterization, does not optimize reservoir development because it fails to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, and carbonate reservoirs in particular. New and emerging technologies, such as geostatistical modeling, rigorous decline curve analysis, reservoir rock typing, and special core analysis can be used to develop a 3-D simulation model for prediction of infill locations. Other technologies, such as inter-well injection tracers and magnetic flow conditioners, can also aid in the efficient evaluation and operation of both injection and producing wells. The purpose of this project was to demonstrate useful and cost effective methods of exploitation of the shallow shelf carbonate reservoirs of the Permian Basin located in West Texas.

  18. 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.

  19. 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

  20. Predicting expatriate job performance for selection purposes: A quantitative review

    NARCIS (Netherlands)

    H.T. van der Molen (Henk); M.Ph. Born (Marise); M.E. Willemsen (Madde)

    2005-01-01

    textabstractThis article meta-analytically reviews empirical studies on the prediction of expatriate job performance. Using 30 primary studies (total N=4,046), it was found that predictive validities of the Big Five were similar to Big Five validities reported for domestic employees. Extraversion,

  1. Predicting Expatriate Job Performance for Selection Purposes: A Quantitative Review

    NARCIS (Netherlands)

    S.T. Mol (Stefan); M.Ph. Born (Marise); M.E. Willemsen (Madde); H.T. van der Molen (Henk)

    2005-01-01

    textabstractThis article meta-analytically reviews empirical studies on the prediction of expatriate job performance. Using 30 primary studies (total N=4046), it was found that predictive validities of the big five were similar to big five validities reported for domestic employees (Barrick & Mount,

  2. 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…

  3. The influence of facies heterogeneity on the doublet performance in low-enthalpy geothermal sedimentary reservoirs

    DEFF Research Database (Denmark)

    Crooijmans, R. A.; Willems, C. J L; Nick, Hamid

    2016-01-01

    A three-dimensional model is used to study the influence of facies heterogeneity on energy production under different operational conditions of low-enthalpy geothermal doublet systems. Process-based facies modelling is utilised for the Nieuwerkerk sedimentary formation in the West Netherlands Basin...... and the energy recovery rate for different discharge rates and the production temperature (Tmin) above which the doublet is working. With respect to the results, we propose a design model to estimate the life time and energy recovery rate of the geothermal doublet. The life time is estimated as a function of N...... errors in predicting the life time of low-enthalpy geothermal systems for N/G values below 70%....

  4. Prediction of Student Performance Through Pretesting in Food and Nutrition

    Science.gov (United States)

    Carruth, Betty Ruth; Lamb, Mina W.

    1971-01-01

    Attempts to develop an objective pretest for identifying students' levels of knowledge in food and nutrition prior to class instruction and for predicting student performance on the final examination. (Editor/MU)

  5. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available Distributed processing offers a way of successfully dealing with computationally demanding applications such as scientific problems. Over the years, researchers have investigated ways to predict the performance of parallel algorithms. Amdahl’s law...

  6. Assessment of performance of survival prediction models for cancer prognosis

    Directory of Open Access Journals (Sweden)

    Chen Hung-Chia

    2012-07-01

    Full Text Available Abstract Background Cancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient’s class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments. Methods We compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models. Results A public breast cancer dataset was used to compare several performance metrics using five prediction models. 1 For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2 The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3 Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results. Conclusions 1 Different performance metrics for evaluation of a survival prediction model may give different conclusions in

  7. Enhanced hydrosuction performance for cohesive sediment removal in low-head reservoirs

    Directory of Open Access Journals (Sweden)

    P. Asiaban

    2017-12-01

    Full Text Available Deposited sediment removal or dredging is generally required in many hydro-system projects. Siphon dredging or hydrosuction bears many advantages including low energy consumption, minor turbidity generation and ability of localized dredging. A new device attached to a regular siphon inlet is introduced which produces a swinging action by means of a simple mechanism. Equipped siphon sweeps a larger area than what a regular siphon does and enhances the hydrosuction performance for cohesive sediment removal. Regular and equipped siphon performances for dredging non-cohesive and cohesive sediments were investigated experimentally. Time to reach equilibrium scour was determined and applied for all the tests. The equipped siphon generated larger scour holes in cohesive sediment type than that of the regular one and enhanced sediment removal process. This could be attributed to the swinging action of the siphon inlet which strikes the scour hole wall and acts against the cohesion property of the sediment.

  8. 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.

  9. The predictive performance and stability of six species distribution models.

    Science.gov (United States)

    Duan, Ren-Yan; Kong, Xiao-Quan; Huang, Min-Yi; Fan, Wei-Yi; Wang, Zhi-Gao

    2014-01-01

    Predicting species' potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs. We collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values. The mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (pSDMs (MAHAL, RF, MAXENT, and SVM) had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points). According to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.

  10. Uncertainty aggregation and reduction in structure-material performance prediction

    Science.gov (United States)

    Hu, Zhen; Mahadevan, Sankaran; Ao, Dan

    2018-02-01

    An uncertainty aggregation and reduction framework is presented for structure-material performance prediction. Different types of uncertainty sources, structural analysis model, and material performance prediction model are connected through a Bayesian network for systematic uncertainty aggregation analysis. To reduce the uncertainty in the computational structure-material performance prediction model, Bayesian updating using experimental observation data is investigated based on the Bayesian network. It is observed that the Bayesian updating results will have large error if the model cannot accurately represent the actual physics, and that this error will be propagated to the predicted performance distribution. To address this issue, this paper proposes a novel uncertainty reduction method by integrating Bayesian calibration with model validation adaptively. The observation domain of the quantity of interest is first discretized into multiple segments. An adaptive algorithm is then developed to perform model validation and Bayesian updating over these observation segments sequentially. Only information from observation segments where the model prediction is highly reliable is used for Bayesian updating; this is found to increase the effectiveness and efficiency of uncertainty reduction. A composite rotorcraft hub component fatigue life prediction model, which combines a finite element structural analysis model and a material damage model, is used to demonstrate the proposed method.

  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. Reading Performance Is Predicted by More Than Phonological Processing

    Directory of Open Access Journals (Sweden)

    Michelle Y. Kibby

    2014-09-01

    Full Text Available We compared three phonological processing components (phonological awareness, rapid automatized naming and phonological memory, verbal working memory, and attention control in terms of how well they predict the various aspects of reading: word recognition, pseudoword decoding, fluency and comprehension, in a mixed sample of 182 children ages 8-12 years. Participants displayed a wide range of reading ability and attention control. Multiple regression was used to determine how well the phonological processing components, verbal working memory, and attention control predict reading performance. All equations were highly significant. Phonological memory predicted word identification and decoding. In addition, phonological awareness and rapid automatized naming predicted every aspect of reading assessed, supporting the notion that phonological processing is a core contributor to reading ability. Nonetheless, phonological processing was not the only predictor of reading performance. Verbal working memory predicted fluency, decoding and comprehension, and attention control predicted fluency. Based upon our results, when using Baddeley’s model of working memory it appears that the phonological loop contributes to basic reading ability, whereas the central executive contributes to fluency and comprehension, along with decoding. Attention control was of interest as some children with ADHD have poor reading ability even if it is not sufficiently impaired to warrant diagnosis. Our finding that attention control predicts reading fluency is consistent with prior research which showed sustained attention plays a role in fluency. Taken together, our results suggest that reading is a highly complex skill that entails more than phonological processing to perform well.

  13. Top-Down, Intelligent Reservoir Model

    Science.gov (United States)

    Mohaghegh, Shahab

    2010-05-01

    Conventional reservoir simulation and modeling is a bottom-up approach. It starts with building a geological model of the reservoir that is populated with the best available petrophysical and geophysical information at the time of development. Engineering fluid flow principles are added and solved numerically so as to arrive at a dynamic reservoir model. The dynamic reservoir model is calibrated using the production history of multiple wells and the history matched model is used to strategize field development in order to improve recovery. Top-Down, Intelligent Reservoir Modeling approaches the reservoir simulation and modeling from an opposite angle by attempting to build a realization of the reservoir starting with the measured well production behavior (history). The production history is augmented by core, log, well test and seismic data in order to increase the accuracy of the Top-Down modeling technique. Although not intended as a substitute for the conventional reservoir simulation of large, complex fields, this novel approach to reservoir modeling can be used as an alternative (at a fraction of the cost) to conventional reservoir simulation and modeling in cases where performing conventional modeling is cost (and man-power) prohibitive. In cases where a conventional model of a reservoir already exists, Top-Down modeling should be considered as a compliment to, rather than a competition for the conventional technique, to provide an independent look at the data coming from the reservoir/wells for optimum development strategy and recovery enhancement. Top-Down, Intelligent Reservoir Modeling starts with well-known reservoir engineering techniques such as Decline Curve Analysis, Type Curve Matching, History Matching using single well numerical reservoir simulation, Volumetric Reserve Estimation and calculation of Recovery Factors for all the wells (individually) in the field. Using statistical techniques multiple Production Indicators (3, 6, and 9 months cum

  14. Volume 3: Characterization of representative reservoirs -- South Marsh Island 73, B35K and B65G Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Young, M.A.; Salamy, S.P.; Reeves, T.K. [BDM-Oklahoma, Inc., Bartlesville, OK (United States); Kimbrell, W.C. [Louisiana State Univ., Baton Rouge, LA (United States). Dept. of Petroleum Engineering; Sawyer, W.K. [Mathematical and Computer Services, Inc., Danville, VA (United States)

    1998-07-01

    This report documents the results of a detailed study of two Gulf of Mexico salt dome related reservoirs and the application of a publicly available PC-based black oil simulator to model the performances of gas injection processes to recover attic oil. The overall objective of the research project is to assess the oil reserve potential that could result from the application of proven technologies to recover bypassed oil from reservoirs surrounding piercement salt domes in the Gulf of Mexico. The specific study objective was to simulate the primary recovery and attic gas injection performance of the two subject reservoirs to: (1) validate the BOAST model; (2) quantify the attic volume; and (3) predict the attic oil recovery potential that could result from additional updip gas injection. The simulation studies were performed on the B-35K Reservoir and the B-65G Reservoir in the South Marsh Island Block 73 Field using data provided by one of the field operators. A modified PC-version of the BOAST II model was used to match the production and injection performances of these reservoirs in which numerous gas injection cycles had been conducted to recover attic oil. The historical performances of the gas injection cycles performed on both the B-35K Reservoir and B-65G Reservoir were accurately matched, and numerous predictive runs were made to define additional potential for attic oil recovery using gas injection. Predictive sensitivities were conducted to examine the impact of gas injection rate, injection volume, post-injection shut-in time, and the staging of gas injection cycles on oil recovery.

  15. 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.

  16. 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)

  17. 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

  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. 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. Mathematical model for dissolved oxygen prediction in Cirata ...

    African Journals Online (AJOL)

    Cirata reservoir is one of the reservoirs which suffer eutrophication with an indication of rapid growth of water hyacinth and mass fish deaths as a result of lack of oxygen. This paper presents the implementation and performance of mathematical model to predict theconcentration of dissolved oxygen in Cirata Reservoir, West ...

  1. 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.

  2. 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.

  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. PMID:25386605

  4. 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.

  5. Fault seal analysis to predict the compartmentalization of gas reservoir: Case study of Steenkool formation Bintuni Basin

    Science.gov (United States)

    Ginanjar, W. C. B.; Haris, A.; Riyanto, A.

    2017-07-01

    This study is aimed to analyze the mechanism of hydrocarbons trapping in the field on a relatively new play in the Bintuni basin particularly Steenkool formation. The first well in this field has been drilled with a shallow target in the Steenkool formation and the drilling is managed to find new gas reserves in the shale-sandstone layer. In the structure of this gas discovery, there is the potential barrier for compartmentalization that draws attention to analyze how the patterns of structural of fault become a part of reservoir compartment. In order to measure the risk associated with prospects on a field bounded by faults, it is important to understand the processes that contribute to fault seal. The method of Fault Seal Analysis (FSA) is one of the methods used for the analysis of the nature of a fault whether the fault is sealing or leaking the fluid flow in the reservoir. Trapping systems that are limited by faults play an important role in creating a trap of hydrocarbon. The ability of a fault to seal fluid is quantitatively reflected by the value of Shale Gouge Ratio (SGR). SGR is the calculation of the amount of fine-grained material that fills fault plane (fault gouge) as a result of the movement mechanism of fault. The result of this study is a valuable resource for the systematic evaluation of the analysis of hydrocarbon prospects in the field.

  6. 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)

  7. The predictive performance and stability of six species distribution models.

    Directory of Open Access Journals (Sweden)

    Ren-Yan Duan

    Full Text Available Predicting species' potential geographical range by species distribution models (SDMs is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs.We collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials. We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values.The mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (p<0.05, while the associated standard deviations and coefficients of variation were larger for BIOCLIM and DOMAIN trials (p<0.05, and the 99% confidence intervals for AUC and Kappa values were narrower for MAHAL, RF, MAXENT, and SVM. Compared to BIOCLIM and DOMAIN, other SDMs (MAHAL, RF, MAXENT, and SVM had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points.According to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.

  8. 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

  9. Predicting course performance in freshman and sophomore physics courses: Women are more predictable than men

    Science.gov (United States)

    McCammon, Susan; Golden, Jeannie; Wuensch, Karl L.

    This study investigated the extent to which thinking skills and mathematical competency would predict the course performance of freshman and sophomore science majors enrolled in physics courses. Multiple-regression equations revealed that algebra and critical thinking skills were the best overall predictors across several physics courses. Although arithmetic skills, math anxiety, and primary mental abilities scores also correlated with performance, they were redundant with the algebra and critical thinking. The most surprising finding of the study was the differential validity by sex; predictor variables were successful in predicting course performance for women but not for men.

  10. 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

    constructed from geological and hydrological data. However, geophysical data are increasingly used to inform hydrogeologic models because they are collected at lower cost and much higher density than geological and hydrological data. Despite increased use of geophysics, it is still unclear whether...... 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...... collecting geophysical data. At a minimum, an analysis should be conducted assuming settings that are favorable for the chosen geophysical method. If the analysis suggests that data collected by the geophysical method is unlikely to improve model prediction performance under these favorable settings...

  11. 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.

  12. 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...

  13. Measuring and Predicting Sleep and Performance During Military Operations

    Science.gov (United States)

    2012-08-23

    stage of sleep. Furthermore, the finding that even relatively brief sleep periods (eg, a 4-hour daily nap following 90 hours of continuous...amounts of SWS obtained. Because normal performance levels are restored recovery sleep periods that include much less sleep time than the amount...Step 1 Step 1 Step 2 work periods sleep periods fatigue level Two-Step Models a b 83 Measuring and Predicting Sleep and Performance During Military

  14. 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.

  15. Gesture Performance in Schizophrenia Predicts Functional Outcome After 6 Months.

    Science.gov (United States)

    Walther, Sebastian; Eisenhardt, Sarah; Bohlhalter, Stephan; Vanbellingen, Tim; Müri, René; Strik, Werner; Stegmayer, Katharina

    2016-11-01

    The functional outcome of schizophrenia is heterogeneous and markers of the course are missing. Functional outcome is associated with social cognition and negative symptoms. Gesture performance and nonverbal social perception are critically impaired in schizophrenia. Here, we tested whether gesture performance or nonverbal social perception could predict functional outcome and the ability to adequately perform relevant skills of everyday function (functional capacity) after 6 months. In a naturalistic longitudinal study, 28 patients with schizophrenia completed tests of nonverbal communication at baseline and follow-up. In addition, functional outcome, social and occupational functioning, as well as functional capacity at follow-up were assessed. Gesture performance and nonverbal social perception at baseline predicted negative symptoms, functional outcome, and functional capacity at 6-month follow-up. Gesture performance predicted functional outcome beyond the baseline measure of functioning. Patients with gesture deficits at baseline had stable negative symptoms and experienced a decline in social functioning. While in patients without gesture deficits, negative symptom severity decreased and social functioning remained stable. Thus, a simple test of hand gesture performance at baseline may indicate favorable outcomes in short-term follow-up. The results further support the importance of nonverbal communication skills in subjects with schizophrenia. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

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

    Science.gov (United States)

    2015-05-01

    COVERED 15Apr2014 - 14Apr2015 4. TITLE AND SUBTITLE Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes 5a. CONTRACT...al., 1982; Kram & Taylor, 1990) that the mass- specific metabolic cost of locomotion varies in a systematic manner with the linear dimensions of the

  17. Prediction of Military Turnover Using Intentions, Satisfaction, and Performance.

    Science.gov (United States)

    Knapp, Deirdre J.; And Others

    Although researchers have examined the link between job attitudes and turnover, some studies claim that civilian samples may not be generalizable to military personnel. This paper addresses two central questions: (1) To what extent does job satisfaction, job performance, and reenlistment intentions predict reenlistment behavior?; (2) To what…

  18. 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.

  19. 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.

  20. 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'…

  1. 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.

  2. Gravity observations for hydrocarbon reservoir monitoring

    OpenAIRE

    Glegola, M.A.

    2013-01-01

    In this thesis the added value of gravity observations for hydrocarbon reservoir monitoring and characterization is investigated. Reservoir processes and reservoir types most suitable for gravimetric monitoring are identified. Major noise sources affecting time-lapse gravimetry are analyzed. The added value of gravity data for reservoir monitoring and characterization is analyzed within closed-loop reservoir management concept. Synthetic 2D and 3D numerical experiments are performed where var...

  3. 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

  4. Systematic review of predictive performance of injury severity scoring tools

    Directory of Open Access Journals (Sweden)

    Tohira Hideo

    2012-09-01

    Full Text Available Abstract Many injury severity scoring tools have been developed over the past few decades. These tools include the Injury Severity Score (ISS, New ISS (NISS, Trauma and Injury Severity Score (TRISS and International Classification of Diseases (ICD-based Injury Severity Score (ICISS. Although many studies have endeavored to determine the ability of these tools to predict the mortality of injured patients, their results have been inconsistent. We conducted a systematic review to summarize the predictive performances of these tools and explore the heterogeneity among studies. We defined a relevant article as any research article that reported the area under the Receiver Operating Characteristic curve as a measure of predictive performance. We conducted an online search using MEDLINE and Embase. We evaluated the quality of each relevant article using a quality assessment questionnaire consisting of 10 questions. The total number of positive answers was reported as the quality score of the study. Meta-analysis was not performed due to the heterogeneity among studies. We identified 64 relevant articles with 157 AUROCs of the tools. The median number of positive answers to the questionnaire was 5, ranging from 2 to 8. Less than half of the relevant studies reported the version of the Abbreviated Injury Scale (AIS and/or ICD (37.5%. The heterogeneity among the studies could be observed in a broad distribution of crude mortality rates of study data, ranging from 1% to 38%. The NISS was mostly reported to perform better than the ISS when predicting the mortality of blunt trauma patients. The relative performance of the ICSS against the AIS-based tools was inconclusive because of the scarcity of studies. The performance of the ICISS appeared to be unstable because the performance could be altered by the type of formula and survival risk ratios used. In conclusion, high-quality studies were limited. The NISS might perform better in the mortality prediction

  5. Prediction of Gas Lubricated Foil Journal Bearing Performance

    Science.gov (United States)

    Carpino, Marc; Talmage, Gita

    2003-01-01

    This report summarizes the progress in the first eight months of the project. The objectives of this research project are to theoretically predict the steady operating conditions and the rotor dynamic coefficients of gas foil journal bearings. The project is currently on or ahead of schedule with the development of a finite element code that predicts steady bearing performance characteristics such as film thickness, pressure, load, and drag. Graphical results for a typical bearing are presented in the report. Project plans for the next year are discussed.

  6. 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

  7. 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

  8. 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

  9. Do coursework summative assessments predict clinical performance? A systematic review.

    Science.gov (United States)

    Terry, Rebecca; Hing, Wayne; Orr, Robin; Milne, Nikki

    2017-02-16

    Two goals of summative assessment in health profession education programs are to ensure the robustness of high stakes decisions such as progression and licensing, and predict future performance. This systematic and critical review aims to investigate the ability of specific modes of summative assessment to predict the clinical performance of health profession education students. PubMed, CINAHL, SPORTDiscus, ERIC and EMBASE databases were searched using key terms with articles collected subjected to dedicated inclusion criteria. Rigorous exclusion criteria were applied to ensure a consistent interpretation of 'summative assessment' and 'clinical performance'. Data were extracted using a pre-determined format and papers were critically appraised by two independent reviewers using a modified Downs and Black checklist with level of agreement between reviewers determined through a Kappa analysis. Of the 4783 studies retrieved from the search strategy, 18 studies were included in the final review. Twelve were from the medical profession and there was one from each of physiotherapy, pharmacy, dietetics, speech pathology, dentistry and dental hygiene. Objective Structured Clinical Examinations featured in 15 papers, written assessments in four and problem based learning evaluations, case based learning evaluations and student portfolios each featured in one paper. Sixteen different measures of clinical performance were used. Two papers were identified as 'poor' quality and the remainder categorised as 'fair' with an almost perfect (k = 0.852) level of agreement between raters. Objective Structured Clinical Examination scores accounted for 1.4-39.7% of the variance in student performance; multiple choice/extended matching questions and short answer written examinations accounted for 3.2-29.2%; problem based or case based learning evaluations accounted for 4.4-16.6%; and student portfolios accounted for 12.1%. Objective structured clinical examinations and written

  10. Temporal prediction errors modulate task-switching performance

    Directory of Open Access Journals (Sweden)

    Roberto eLimongi

    2015-08-01

    Full Text Available We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus’ onset times modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI, causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected, which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad-hoc concepts such as executive control is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching.

  11. 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.

  12. 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.

  13. 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

  14. 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

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

    Directory of Open Access Journals (Sweden)

    Habib U Jan

    Full Text Available 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

  16. Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

    Science.gov (United States)

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

    2015-01-01

    Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

  17. 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).

  18. Modular Resource Centric Learning for Workflow Performance Prediction

    OpenAIRE

    Singh, Alok; Nguyen, Mai; Purawat, Shweta; Crawl, Daniel; Altintas, Ilkay

    2017-01-01

    Workflows provide an expressive programming model for fine-grained control of large-scale applications in distributed computing environments. Accurate estimates of complex workflow execution metrics on large-scale machines have several key advantages. The performance of scheduling algorithms that rely on estimates of execution metrics degrades when the accuracy of predicted execution metrics decreases. This in-progress paper presents a technique being developed to improve the accuracy of pred...

  19. 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...... implementation consisting of a distributed PI controller structure, both in terms of minimising the overall cost but also in terms of the ability to minimise deviation, which is the classical objective....

  20. Prediction of Cone Crusher Performance Considering Liner Wear

    Directory of Open Access Journals (Sweden)

    Yanjun Ma

    2016-12-01

    Full Text Available Cone crushers are used in the aggregates and mining industries to crush rock material. The pressure on cone crusher liners is the key factor that influences the hydraulic pressure, power draw and liner wear. In order to dynamically analyze and calculate cone crusher performance along with liner wear, a series of experiments are performed to obtain the crushed rock material samples from a crushing plant at different time intervals. In this study, piston die tests are carried out and a model relating compression coefficient, compression ratio and particle size distribution to a corresponding pressure is presented. On this basis, a new wear prediction model is proposed combining the empirical model for predicting liner wear with time parameter. A simple and practical model, based on the wear model and interparticle breakage, is presented for calculating compression ratio of each crushing zone along with liner wear. Furthermore, the size distribution of the product is calculated based on existing size reduction process model. A method of analysis of product size distribution and shape in the crushing process considering liner wear is proposed. Finally, the validity of the wear model is verified via testing. The result shows that there is a significant improvement of the prediction of cone crusher performance considering liner wear as compared to the previous model.

  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. Predictions and Performance on the PACT Teaching Event: Case Studies of High and Low Performers

    Science.gov (United States)

    Sandholtz, Judith Haymore

    2012-01-01

    In an earlier study, the author and her colleague explored the extent to which supervisors' perspectives about candidates' performance corresponded with outcomes from a summative performance assessment (Sandholtz & Shea, 2012). They specifically examined the relationship between university supervisors' predictions and candidates' performance…

  3. 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)

  4. 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.

  5. Fuzzy regression modeling for tool performance prediction and degradation detection.

    Science.gov (United States)

    Li, X; Er, M J; Lim, B S; Zhou, J H; Gan, O P; Rutkowski, L

    2010-10-01

    In this paper, the viability of using Fuzzy-Rule-Based Regression Modeling (FRM) algorithm for tool performance and degradation detection is investigated. The FRM is developed based on a multi-layered fuzzy-rule-based hybrid system with Multiple Regression Models (MRM) embedded into a fuzzy logic inference engine that employs Self Organizing Maps (SOM) for clustering. The FRM converts a complex nonlinear problem to a simplified linear format in order to further increase the accuracy in prediction and rate of convergence. The efficacy of the proposed FRM is tested through a case study - namely to predict the remaining useful life of a ball nose milling cutter during a dry machining process of hardened tool steel with a hardness of 52-54 HRc. A comparative study is further made between four predictive models using the same set of experimental data. It is shown that the FRM is superior as compared with conventional MRM, Back Propagation Neural Networks (BPNN) and Radial Basis Function Networks (RBFN) in terms of prediction accuracy and learning speed.

  6. 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.

  7. Predicting visual performance from optical quality metrics in keratoconus.

    Science.gov (United States)

    Schoneveld, Paul; Pesudovs, Konrad; Coster, Douglas J

    2009-05-01

    The aim was to identify optical quality metrics predictive of visual performance in eyes with keratoconus and penetrating keratoplasty (PK) for keratoconus. Fifty-four participants were recruited for this prospective, cross-sectional study. Data were collected from one eye of each participant: 26 keratoconus, 10 PK and 18 normal eyes: average age (mean +/- standard deviation) 45.2 +/- 10.6 years and 56 per cent female. Visual performance was tested by 10 methods including visual acuity (VA), both high and low contrast (HC- and LC-) and high and low luminance (LL-), and Pelli-Robson contrast sensitivity, all tested with and without glare. Corneal first surface wavefront aberrations were calculated from Orbscan corneal topographic data using VOLPro software v7.08 (Sarver and Associates) as a tenth-order Zernike expansion across three, 4.0 mm and 5.0 mm pupils and converted into 31 optical quality metrics. Pearson correlation coefficients and linear regression were used to relate wavefront aberration metrics to visual performance. Visual performance was highly predictable from optical quality with the average correlation of the order of 0.5. Pupil fraction metrics (for example, PFWc) were responsible for all of the highest correlations at large pupils for example, with HCVA (r = 0.80), LCVA (r = 0.80) and LLLCVA (r = 0.75). Image plane metrics, derived from the optical transfer function (OTF) were responsible for most of the highest correlations at smaller pupils for example, volume under the OTF (VOTF) with HCVA (r = 0.76) and LCVA (r = 0.73). As in normal eyes, visual performance in keratoconus was predicable from optical quality; albeit by different metrics. Optical quality metrics predictive of visual performance in normal eyes, for example, visual Strehl, lack the dynamic range to represent visual performance in highly aberrated eyes with keratoconus. Optical quality outcomes for keratoconus could be reported using many different metrics, but pupil fraction

  8. Reservoir Cathode for Electric Space Propulsion Project

    Data.gov (United States)

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

  9. 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.

  10. Performance predictions and manufacturing concerns of burnable poison rods

    International Nuclear Information System (INIS)

    Copeland, R.A.; Buescher, B.J.

    1977-01-01

    Burnable poison rods for reactors designed by B and W consist of low density pellets, composed of boron carbide dispersed in an alumina matrix (Al 2 O 3 --B 4 C), which are contained in Zircaloy-4 tubes. To predict reliable operation of these rods, the irradiation behavior of the components must be known. Performance models were developed based on experimental irradiation data. During rod fabrication, care must be taken to limit the amount of hydrogen in the rod because of the propensity of Zircaloy to hydride in the presence of high levels of hydrogen. Furthermore, the hygroscopic nature of alumina dictates that care must be taken to avoid moisture (a primary source of hydrogen) in the rods. Manufacturing and quality testing procedures have been developed to provide conformance to the design criteria. Examinations have been performed on irradiated burnable poison rods which verify the adequacy of both performance models and manufacturing procedures

  11. Advanced wet--dry cooling tower concept performance prediction

    Energy Technology Data Exchange (ETDEWEB)

    Snyder, T.; Bentley, J.; Giebler, M.; Glicksman, L.R.; Rohsenow, W.M.

    1977-01-01

    The purpose of this year's work has been to test and analyze the new dry cooling tower surface previously developed. The model heat transfer test apparatus built last year has been instrumented for temperature, humidity and flow measurement and performance has been measured under a variety of operating conditions. Tower Tests showed approximately 40 to 50% of the total energy transfer as taking place due to evaporation. This can be compared to approximately 80 to 85% for a conventional wet cooling tower. Comparison of the model tower test results with those of a computer simulation has demonstrated the validity of that simulation and its use as a design tool. Computer predictions have been made for a full-size tower system operating at several locations. Experience with this counterflow model tower has suggested that several design problems may be avoided by blowing the cooling air horizontally through the packing section. This crossflow concept was built from the previous counterflow apparatus and included the design and fabrication of new packing plates. Instrumentation and testing of the counterflow model produced data with an average experimental error of 10%. These results were compared to the predictions of a computer model written for the crossflow configuration. In 14 test runs the predicted total heat transfer differed from the measured total heat transfer by no more than 8% with most runs coming well within 5%. With the computer analogy's validity established, it may now be used to help predict the performance of fullscale wet-dry towers.

  12. 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

  13. 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.

  14. 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.

  15. 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

  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 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.

  17. 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

  18. 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.

  19. 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.

  20. 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)

  1. Performance Prediction of Wind Power Turbine by CAD Analysis

    International Nuclear Information System (INIS)

    Kim, Jongho; Kim, Jongbong; Oh, Younglok

    2013-01-01

    The performance of a vertical-type wind power generator system was predicted by CAD analysis. In the analysis, the reaction torque was calculated for a given rotational speed of the blades. The blade torque of a wind power system was obtained for various rotational speeds, and the generation power was calculated using the obtained torque and the rotational speed. The optimum generator specification, therefore, could be decided using the relationship between the generated power and the rotational speeds. The effects of the number of blades and blade shapes on the generation power were also investigated. Finally, the analysis results were compared with the experimental results

  2. 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

  3. A Viscoplastic Stress Relaxation Model for Predicting Variations of the Least Principal Stress With Depth in Unconventional Reservoirs

    Science.gov (United States)

    Zoback, M. D.; Xu, S.; Rassouli, F.; Ma, X.

    2016-12-01

    In this paper we extend the viscoplastic stress relaxation model of Sone and Zoback (Jour. Petrol. Sci. and Eng., 2014) for predicting variations of least principal stress with stress and its impact on the vertical propagation of hydraulic fractures. Viscoplastic stress relaxation in clay-rich (or diagenetically immature) sedimentary rocks makes the stress field more isotropic. In normal faulting and strike-slip faulting environments, this causes the least principal stress to increase making such formations likely barriers to vertical hydraulic fracture growth. In order to predict the magnitude of viscoplastic stress relaxation in different unconventional formations, we generalize a constitutive law developed from a wide range of creep experiments in our lab over the past several years and apply it to areas of stacked pay in Oklahoma and Texas. Using frac gradients were measured from minifrac and DFIT (Diagnostic Fracture Injection Test) experiments. The viscoplastic model does a good job of explaining vertical hydraulic fracture propagation, as indicated by the distribution of microseismic events recorded during stimulation.

  4. 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. PMID:28955215

  5. 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.

  6. Planning for Predictable Network Performance in the ATLAS TDAQ

    CERN Document Server

    Meirosu, C; Topurov, A; Al-Shabibi, A; Computing In High Energy and Nuclear Physics

    2006-01-01

    The Trigger and Data Acquisition System of the ATLAS experiment is currently being installed at CERN. A significant amount of computing resources will be deployed in the Online computing system. More than 3000 high-performance computers will be supported by networks composed of about 200 Ethernet switches. The architecture of the networks was optimised for the particular traffic profile generated by data transfer protocols with real-time delivery constraints. In this paper, we summarise the operational requirements imposed on the TDAQ networks. We describe the architecture of the network management solution that fulfils the complete set of requirements. Commercial and custom-developed applications will be integrated in a solution that will provide a maximum of relevant information to the physics operator on shift and enable the networking team to analyse trends and predict the network performance.

  7. 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.

  8. Do study strategies predict academic performance in medical school?

    Science.gov (United States)

    West, Courtney; Sadoski, Mark

    2011-07-01

     Study strategies, such as time and study management techniques, seem to be consistently related to achievement even when aptitude is controlled for, but the picture is not entirely clear. As there is limited research in this area, we explored the relative strengths of academic aptitude, as measured by the Medical College Admission Test (MCAT), undergraduate grade point average (UGPA) and study strategies, as measured by the Learning and Study Strategies Inventory (LASSI), in predicting academic performance in 106 students in the first semester of an integrated curriculum.  Our purpose was to determine whether relationships could be identified between academic aptitude, study strategies and academic performance which would enable us to provide students with feedback in certain skill areas in order to maximise achievement. Data analysis consisted of four multiple regression analyses. The criterion variables were: semester overall final average, semester written examination average, semester practical examination average, and percentage correct on a customised National Board of Medical Examiners (NBME) examination. The predictor variables in each regression were: MCAT score; UGPA; and subscores on the 10 LASSI subscales for Anxiety, Attitude, Motivation, Concentration, Information Processing, Self-Testing, Selecting Main Idea, Study Aids, Time Management and Test-Taking Strategies. The results of three regressions indicated that two study skills, time management and self-testing, were generally stronger predictors of first-semester academic performance than aptitude. Improving the prioritisation and organisation of study time and teaching students to predict, compose and answer their own questions when studying may help to advance student performance regardless of student aptitude, especially on course-specific examinations. © Blackwell Publishing Ltd 2011.

  9. The Ahuachapan geothermal field, El Salvador: Exploitation model, performance predictions, economic analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ripperda, M.; Bodvarsson, G.S.; Lippmann, M.J.; Witherspoon, P.A.; Goranson, C.

    1991-05-01

    The Earth Sciences Division of Lawrence Berkeley Laboratory (LBL) is conducting a reservoir evaluation study of the Ahuachapan geothermal field in El Salvador. This work is being performed in cooperation with the Comision Ejecutiva Hidroelectrica del Rio Lempa (CEL) and the Los Alamos National Laboratory (LANL) with funding from the US Agency for International Development (USAID). This report describes the work done during the second year of the study (FY89--90). The first year's report included (1) the development of geological and conceptual models of the field, (2) the evaluation of the reservoir's initial thermodynamic and chemical conditions and their changes during exploitation, (3) the evaluation of interference test data and the observed reservoir pressure decline and (4) the development of a natural state model for the field. In the present report the results of reservoir engineering studies to evaluate different production-injection scenarios for the Ahuachapan geothermal field are discussed. The purpose of the work was to evaluate possible reservoir management options to enhance as well as to maintain the productivity of the field during a 30-year period (1990--2020). The ultimate objective was to determine the feasibility of increasing the electrical power output at Ahuachapan from the current level of about 50 MW{sub e} to the total installed capacity of 95 MW{sub e}. 20 refs., 75 figs., 10 tabs.

  10. 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.

  11. 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.

  12. Children's construction task performance and spatial ability: controlling task complexity and predicting mathematics performance.

    Science.gov (United States)

    Richardson, Miles; Hunt, Thomas E; Richardson, Cassandra

    2014-12-01

    This paper presents a methodology to control construction task complexity and examined the relationships between construction performance and spatial and mathematical abilities in children. The study included three groups of children (N = 96); ages 7-8, 10-11, and 13-14 years. Each group constructed seven pre-specified objects. The study replicated and extended previous findings that indicated that the extent of component symmetry and variety, and the number of components for each object and available for selection, significantly predicted construction task difficulty. Results showed that this methodology is a valid and reliable technique for assessing and predicting construction play task difficulty. Furthermore, construction play performance predicted mathematical attainment independently of spatial ability.

  13. 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.

  14. 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

  15. 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

  16. Predicting performance in competitive apnea diving. Part III: deep diving.

    Science.gov (United States)

    Schagatay, Erika

    2011-12-01

    The first of these reviews described the physiological factors defining the limits of static apnea, while the second examined performance in apneic distance swimming. This paper reviews the factors determining performance in depth disciplines, where hydrostatic pressure is added to the stressors associated with apnea duration and physical work. Apneic duration is essential for performance in all disciplines, and is prolonged by any means that increases gas storage or tolerance to asphyxia or reduces metabolic rate. For underwater distance swimming, the main challenge is to restrict metabolism despite the work of swimming, and to redirect blood flow to allow the most vital functions. Here, work economy, local tissue energy and oxygen stores, anaerobic capacity of the muscles, and possibly technical improvements will be essential for further development. In the depth disciplines, direct pressure effects causing barotrauma, the narcotic effects of gases, decompression sickness (DCS) and possibly air embolism during ascent need to be taken into account, as does the risk of hypoxia when the dive cannot be rapidly interrupted before the surface is reached again. While in most deep divers apneic duration is not the main limitation thus far, greater depths may call for exceptionally long apneas and slower ascents to avoid DCS. Narcotic effects may also affect the ultimate depth limit, which the divers currently performing 'constant weight with fins' dives predict to be around 156 metres' sea water. To reach these depths, serious physiological challenges have to be met, technical developments needed and safety procedures developed concomitantly.

  17. 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.

  18. Challenges of reservoir properties and production history matching in a CHOPS reservoir study

    Energy Technology Data Exchange (ETDEWEB)

    Alam, Mahbub [Department of Geoscience, University of Calgary (Canada)

    2011-07-01

    In order to meet increasing world energy demand, wells have to be drilled within very thin reservoir beds. This paper, we present one of the solutions for optimizing the reservoir characterization. Reservoir characterization is the process between the discovery of a property and the reservoir management phase. Principal data for reservoir modeling are: 4D Seismic interpretation, wireline log interpretation, core analysis, and petrophysical analysis. Reservoir conditions, perforation and completion technology are the key issues to the production rate of cold production. Reservoir modeling intends to minimize the risk factor, maximize production, and help determine the location for infill drillings. Cold heavy oil production with sand (CHOPS) is a method for enhancing primary production from heavy oil reservoirs. Gravitational forces, natural fluid pressure gradients and foamy oil flow phenomena are the major driving forces of the CHOPS mechanism. Finally, Reservoir characterization allows better understanding of permeability and porosity prediction.

  19. Sensitivity Studies on Productivity Performance from 3D Heterogeneous Reservoir Model Based on the L-Pad Gas Hydrate Accumulation in Prudhoe Bay Unit, North Slope Alaska

    Science.gov (United States)

    Myshakin, E. M.; Ajayi, T.; Seol, Y.; Boswell, R.

    2016-12-01

    Three-dimensional reservoir model of the "L-Pad" hydrate deposit located in the Prudhoe Bay region of the Alaska's North Slope was created including four stratigraphic units; silty shale overburden, hydrate-bearing D sand, inter-reservoir silty shale, hydrate-bearing C sand, and silty shale underburden. The model incorporates the actual geological settings, accounts for the presence of faults, reservoir dip, the hydrate-water contact in the C sand. Geostatistical porosity distributions in D and C sands conditioned to log data from 78 wells drilled in the vicinity of the Prudhoe Bay "L-pad" were developed providing vertical and lateral 3D heterogeneity in porosity and porosity-dependent hydrate saturation and intrinsic permeability. Gas production potential was estimated using a conventional vertical wellbore completion and a deviated toe-down wellbore perforated through both sand units to induce hydrate depressurization at a constant bottom-hole pressure. The results have shown the greater performance of the deviated well design over the vertical one. The scenarios involving simultaneous and sequential hydrate dissociation in sand units were explored and the effect of the underlying aquifer in the C sand was estimated. Sensitivity analysis has demonstrated that hydraulic communication with over- and underlying shale units affects production in the beginning of depressurization due to competitive water influx into producing mobile flow and could suppress efficient hydrate decomposition resulting in production lag. Another important factor greatly influencing the productivity performance is the effective permeability of hydrate-bearing sediment controlled by the relative permeability function. The results call for the necessity of thorough fundamental studies to understand multi-phase flow in hydrate-bearing sediments with different hydrate precipitation habits.

  20. IMPROVED OIL RECOVERY IN MISSISSIPPIAN CARBONATE RESERVOIRS OF KANSAS - NEAR TERM - CLASS 2

    Energy Technology Data Exchange (ETDEWEB)

    Timothy R. Carr; Don W. Green; G. Paul Willhite

    2000-04-30

    This annual report describes progress during the final year of the project entitled ''Improved Oil Recovery in Mississippian Carbonate Reservoirs in Kansas''. This project funded under the Department of Energy's Class 2 program targets improving the reservoir performance of mature oil fields located in shallow shelf carbonate reservoirs. The focus of the project was development and demonstration of cost-effective reservoir description and management technologies to extend the economic life of mature reservoirs in Kansas and the mid-continent. As part of the project, tools and techniques for reservoir description and management were developed, modified and demonstrated, including PfEFFER spreadsheet log analysis software. The world-wide-web was used to provide rapid and flexible dissemination of the project results through the Internet. A summary of demonstration phase at the Schaben and Ness City North sites demonstrates the effectiveness of the proposed reservoir management strategies and technologies. At the Schaben Field, a total of 22 additional locations were evaluated based on the reservoir characterization and simulation studies and resulted in a significant incremental production increase. At Ness City North Field, a horizontal infill well (Mull Ummel No.4H) was planned and drilled based on the results of reservoir characterization and simulation studies to optimize the location and length. The well produced excellent and predicted oil rates for the first two months. Unexpected presence of vertical shale intervals in the lateral resulted in loss of the hole. While the horizontal well was not economically successful, the technology was demonstrated to have potential to recover significant additional reserves in Kansas and the Midcontinent. Several low-cost approaches were developed to evaluate candidate reservoirs for potential horizontal well applications at the field scale, lease level, and well level, and enable the small

  1. Improving reservoir conformance using gelled polymer systems

    Energy Technology Data Exchange (ETDEWEB)

    Green, D.W.; Willhite, G.P.

    1993-04-09

    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 (KUSPI) system that gels as a function of pH, the chromium-based system where polyacrylamide and xanthan are crosslinked by CR(III) and an organic crosslinked system. Development of the KUSPI system and evaluation and identification of a suitable organic crosslinked system will be done. The 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. Accomplishments for this period are presented for the following tasks: development and selection of gelled polymer systems, physical and chemical characterization of gel systems; and mathematical modeling of gel systems.

  2. 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.

  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. Design and Performance Analysis of Incremental Networked Predictive Control Systems.

    Science.gov (United States)

    Pang, Zhong-Hua; Liu, Guo-Ping; Zhou, Donghua

    2016-06-01

    This paper is concerned with the design and performance analysis of networked control systems with network-induced delay, packet disorder, and packet dropout. Based on the incremental form of the plant input-output model and an incremental error feedback control strategy, an incremental networked predictive control (INPC) scheme is proposed to actively compensate for the round-trip time delay resulting from the above communication constraints. The output tracking performance and closed-loop stability of the resulting INPC system are considered for two cases: 1) plant-model match case and 2) plant-model mismatch case. For the former case, the INPC system can achieve the same output tracking performance and closed-loop stability as those of the corresponding local control system. For the latter case, a sufficient condition for the stability of the closed-loop INPC system is derived using the switched system theory. Furthermore, for both cases, the INPC system can achieve a zero steady-state output tracking error for step commands. Finally, both numerical simulations and practical experiments on an Internet-based servo motor system illustrate the effectiveness of the proposed method.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  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. 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

  13. 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

  14. 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.

  15. 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

  16. A reservoir simulation approach for modeling of naturally fractured reservoirs

    Directory of Open Access Journals (Sweden)

    H. Mohammadi

    2012-12-01

    Full Text Available In this investigation, the Warren and Root model proposed for the simulation of naturally fractured reservoir was improved. A reservoir simulation approach was used to develop a 2D model of a synthetic oil reservoir. Main rock properties of each gridblock were defined for two different types of gridblocks called matrix and fracture gridblocks. These two gridblocks were different in porosity and permeability values which were higher for fracture gridblocks compared to the matrix gridblocks. This model was solved using the implicit finite difference method. Results showed an improvement in the Warren and Root model especially in region 2 of the semilog plot of pressure drop versus time, which indicated a linear transition zone with no inflection point as predicted by other investigators. Effects of fracture spacing, fracture permeability, fracture porosity, matrix permeability and matrix porosity on the behavior of a typical naturally fractured reservoir were also presented.

  17. 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.

  18. Reservoir Simulations of Low-Temperature Geothermal Reservoirs

    Science.gov (United States)

    Bedre, Madhur Ganesh

    The eastern United States generally has lower temperature gradients than the western United States. However, West Virginia, in particular, has higher temperature gradients compared to other eastern states. A recent study at Southern Methodist University by Blackwell et al. has shown the presence of a hot spot in the eastern part of West Virginia with temperatures reaching 150°C at a depth of between 4.5 and 5 km. This thesis work examines similar reservoirs at a depth of around 5 km resembling the geology of West Virginia, USA. The temperature gradients used are in accordance with the SMU study. In order to assess the effects of geothermal reservoir conditions on the lifetime of a low-temperature geothermal system, a sensitivity analysis study was performed on following seven natural and human-controlled parameters within a geothermal reservoir: reservoir temperature, injection fluid temperature, injection flow rate, porosity, rock thermal conductivity, water loss (%) and well spacing. This sensitivity analysis is completed by using ‘One factor at a time method (OFAT)’ and ‘Plackett-Burman design’ methods. The data used for this study was obtained by carrying out the reservoir simulations using TOUGH2 simulator. The second part of this work is to create a database of thermal potential and time-dependant reservoir conditions for low-temperature geothermal reservoirs by studying a number of possible scenarios. Variations in the parameters identified in sensitivity analysis study are used to expand the scope of database. Main results include the thermal potential of reservoir, pressure and temperature profile of the reservoir over its operational life (30 years for this study), the plant capacity and required pumping power. The results of this database will help the supply curves calculations for low-temperature geothermal reservoirs in the United States, which is the long term goal of the work being done by the geothermal research group under Dr. Anderson at

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. Predicting Student Academic Performance in an Engineering Dynamics Course: A Comparison of Four Types of Predictive Mathematical Models

    Science.gov (United States)

    Huang, Shaobo; Fang, Ning

    2013-01-01

    Predicting student academic performance has long been an important research topic in many academic disciplines. The present study is the first study that develops and compares four types of mathematical models to predict student academic performance in engineering dynamics--a high-enrollment, high-impact, and core course that many engineering…

  4. Stressor-response modeling using the 2D water quality model and regression trees to predict chlorophyll-a in a reservoir system

    Science.gov (United States)

    Park, Yongeun; Pachepsky, Yakov A.; Cho, Kyung Hwa; Jeon, Dong Jin; Kim, Joon Ha

    2015-10-01

    To control algal blooms, the stressor-response relationships between water quality metrics, environmental variables, and algal growth need to be better understood and modeled. Machine-learning methods have been suggested as means to express the stressor-response relationships that are found when applying mechanistic water quality models. The objective of this work was to evaluate the efficiency of regression trees in the development of a stressor-response model for chlorophyll-a (Chl-a) concentrations, using the results from site-specific mechanistic water quality modeling. The 2-dimensional hydrodynamic and water quality model (CE-QUAL-W2) model was applied to simulate water quality using four-year observational data and additional scenarios of air temperature increases for the Yeongsan Reservoir in South Korea. Regression tree modeling was applied to the results of these simulations. Given the well-expressed seasonality in the simulated Chl-a dynamics, separate regression trees were developed for months from May to September. The regression trees provided a reasonably accurate representation of the stressor-response dependence generated by the CE-QUAL-W2 model. Different stressors were then selected as split variables for different months, and, in most cases, splits by the same stressor variable yielded the same correlation sign between the variable and the Chl-a concentration. Compared to physical variables, nutrient content appeared to better predict Chl-a responses. The highest Chl-a temperature sensitivities were found for May and June. Regression tree splits based on ammonium concentration resulted in a consistent trend of greater sensitivity in the groups of samples with higher ammonium concentrations. Regression tree models provided a transparent visual representation of the stressor-response relationships for Chl-a and its sensitivity. Overall, the representation of relationships using classification and regression tools can be considered a useful

  5. 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.

  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. GPM Microwave Imager Design, Predicted Performance and Status

    Science.gov (United States)

    Krimchansky, Sergey; Newell, David

    2010-01-01

    The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (t.JASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dual-frequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element of GPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

  8. Individual Differences in Nonsymbolic Ratio Processing Predict Symbolic Math Performance.

    Science.gov (United States)

    Matthews, Percival G; Lewis, Mark Rose; Hubbard, Edward M

    2016-02-01

    What basic capacities lay the foundation for advanced numerical cognition? Are there basic nonsymbolic abilities that support the understanding of advanced numerical concepts, such as fractions? To date, most theories have posited that previously identified core numerical systems, such as the approximate number system (ANS), are ill-suited for learning fraction concepts. However, recent research in developmental psychology and neuroscience has revealed a ratio-processing system (RPS) that is sensitive to magnitudes of nonsymbolic ratios and may be ideally suited for supporting fraction concepts. We provide evidence for this hypothesis by showing that individual differences in RPS acuity predict performance on four measures of mathematical competence, including a university entrance exam in algebra. We suggest that the nonsymbolic RPS may support symbolic fraction understanding much as the ANS supports whole-number concepts. Thus, even abstract mathematical concepts, such as fractions, may be grounded not only in higher-order logic and language, but also in basic nonsymbolic processing abilities. © The Author(s) 2015.

  9. 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)

  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. 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

  12. 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

  13. Artificial neural network modeling of dissolved oxygen in reservoir.

    Science.gov (United States)

    Chen, Wei-Bo; Liu, Wen-Cheng

    2014-02-01

    The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.

  14. 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

  15. Radio link design framework for WSN deployment and performance prediction

    Science.gov (United States)

    Saponara, Sergio; Giannetti, Filippo

    2017-05-01

    For an easy implementation of wireless sensor and actuator networks (WSAN), the state-of-the-art is offering single-chip solutions embedding in the same device a microcontroller core with a wireless transceiver. These internet-on-chip devices support different protocols (Bluetooth, ZigBee, Bluetooth Low Energy, sub- GHz links), from about 300 MHz to 6 GHz, with max. sustained bit-rates from 250 kb/s (sub-GHz links) to 4 Mb/s (Wi-Fi), and different trade-offs between RX sensitivity (from -74 to -100 dBm), RX noise figure (few dB to 10 dB), maximum TX power (from 0 to 22 dBm), link distances, power consumption levels (from few mW to several hundreds of mW). One limit for their successful application is the missing of an easy-to-use modeling and simulation environment to plan their deployment. The need is to predict, before installing a network, at which distances the sensors can be deployed, the real achievable bit-rate, communication latency, outage probability, power consumption, battery duration. To this aim, this paper presents the H2AWKS (Harsh environment and Hardware Aware Wireless linK Simulator) simulator, which allows the planning of a WSAN taking into account environment constraints and hardware parameters. Applications of H2AWKS to real WSAN case studies prove that it is an easy to use simulation environment, which allows design exploration of the system performance of a WSAN as a function of the operating environment and of the hardware parameters of the used devices.

  16. Use of Operational Climate Forecasts in Reservoir Management and Operation

    Science.gov (United States)

    Arumugam, S.; Lall, U.

    2005-12-01

    Seasonal streamflow forecasts contingent on climate information are essential for short-term planning and for setting up contingency measures during extreme years. Similarly, monthly updates of streamflow forecasts are useful in quantifying surplus and shortfall in addressing the change in streamflow potential during the season. In this study, an operational streamflow forecasts for managing the Angat Reservoir System, Philippines, is developed using the precipitation forecasts from Atmospheric General Circulation Models (AGCM) that are forced by persisted Sea Surface Temperature (SST) conditions. The methodology employs principal components regression (PCR) to downscale the AGCM predicted precipitation fields to monthly streamflow forecasts. By performing retrospective analyses that combines streamflow forecasts with a dynamic water allocation model, we show that use of updated climate forecasts in reservoir operation results in increased reservoir system yields in comparison to using the seasonal streamflow forecasts alone. Revising the reservoir operation strategy based on updated streamflow forecasts is particularly critical in hydropower systems, since the increased yields from reduced spillage could be effectively utilized for power generation during above-normal inflow years. Further, analyzing the system performance under different scenarios of storage and demand, we show that the utility of climate information based reservoir inflow forecasts is more pronounced for systems with low storage to demand ratio.

  17. Prediction of hybrid performance in maize with transcriptome data

    OpenAIRE

    Zenke-Philippi, Carola Anna Luise

    2017-01-01

    Most studies on genomic prediction of hybrids employ genetic markers as the main carrier of information. Very few use transcriptomic or metabolomic data despite the fact that the end product of gene expression, i.e., the protein, might carry more information than genetic markers. The main goal of the present study was therefore to investigate whether gene expression profiles can be employed successfully for hybrid prediction in maize. With RR-BLUP, similar accuracies were found for ALFP ma...

  18. Numerical Performance Prediction of a Miniature Ramjet at Mach 4

    Science.gov (United States)

    2012-09-01

    measured using cryogenic strain gauges arranged in a Wheatstone bridge . A CFD cold-flow drag prediction was compared against this measured drag...cryogenic strain gauges arranged in a Wheatstone bridge . A CFD cold-flow drag prediction was compared against this measured drag force to establish...ramjet model mounted in the SSWT ....................................... 31  Figure 31.  Wheatstone bridge for potential difference measurements

  19. Prediction of Human Glomerular Filtration Rate from Preterm Neonates to Adults: Evaluation of Predictive Performance of Several Empirical Models.

    Science.gov (United States)

    Mahmood, Iftekhar; Staschen, Carl-Michael

    2016-03-01

    The objective of this study was to evaluate the predictive performance of several allometric empirical models (body weight dependent, age dependent, fixed exponent 0.75, a data-dependent single exponent, and maturation models) to predict glomerular filtration rate (GFR) in preterm and term neonates, infants, children, and adults without any renal disease. In this analysis, the models were developed from GFR data obtained from inulin clearance (preterm neonates to adults; n = 93) and the predictive performance of these models were evaluated in 335 subjects (preterm neonates to adults). The primary end point was the prediction of GFR from the empirical allometric models and the comparison of the predicted GFR with measured GFR. A prediction error within ±30% was considered acceptable. Overall, the predictive performance of the four models (BDE, ADE, and two maturation models) for the prediction of mean GFR was good across all age groups but the prediction of GFR in individual healthy subjects especially in neonates and infants was erratic and may be clinically unacceptable.

  20. 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

    2018-04-03

    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.

  1. Using dynamical uncertainty models estimating uncertainty bounds on power plant performance prediction

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Stoustrup, Jakob; Mataji, B.

    2007-01-01

    of the prediction error. These proposed dynamical uncertainty models result in an upper and lower bound on the predicted performance of the plant. The dynamical uncertainty models are used to estimate the uncertainty of the predicted performance of a coal-fired power plant. The proposed scheme, which uses dynamical...

  2. First Assessments of Predicted ICESat-2 Performance Using Aircraft Data

    Science.gov (United States)

    Neumann, Thomas; Markus, Thorsten; Cook, William; Hancock, David; Brenner, Anita; Kelly, Brunt; DeMarco, Eugenia; Reed, Daniel; Walsh, Kaitlin

    2012-01-01

    The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard

  3. Real gas effects on the prediction of ram accelerator performance

    Science.gov (United States)

    Bauer, P.; Knowlen, C.; Bruckner, A.

    The analysis of ram accelerator performance is based on one-dimensional modelling of the flow process that propels the projectile. The conservation equations are applied to a control volume travelling with the projectile, and quasi-steady flow is assumed. To date the solution obtained, namely the generalized thrust equation, has been based on the ideal gas assumption. At the high level of pressure that is encountered during the ram accelerator process, this assumption cannot be regarded as adequate. Thus, a more appropriate equation of state (EOS) should be used instead. Depending upon the level of pressure, several equations of state are available for dense gaseous energetic materials. The virial type of EOS can be more or less sophisticated, depending upon the extent of complexity of the intermolecular modelling, and turns out to be totally appropriate for most gaseous explosive mixtures that have been investigated at moderate initial pressures, i.e., less than 10MPa. In the present case the Boltzmann EOS was applied. It is based on very simplified molecular interactions, which makes it relatively easy to use in calculations. Moreover, the energetic EOS needs to be taken into account. This concerns all the calorimetric coefficients, as well as the thermodynamic parameters, which can no longer be expressed as only a function of temperature. The higher the pressure level, the more sophisticated these corrections become, but the main relationships that account for real gas effects are basically the same. These include the use of a general form of analytical operators applied to correct the thermodynamic functions and coefficients. The equations governing the one-dimensional model were taken as a basis for the real gas corrections and were solved analytically. The parameters which play the most crucial roles in this correction can thus be highlighted. A complete set of equations involving the real gas effects are presented in this paper. The QUARTET code was used in

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. 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 ...

  9. Academic Progress Scores to Predict Performance on a State Assessment

    Science.gov (United States)

    Curry, Mitchell

    2016-01-01

    This quantitative study examined seventh-grade reading scores to determine the extent to which certain demographic variables (race/ethnicity, gender, socioeconomic status) explain and MAP reading scores predict reading scores on the State of Texas Assessment of Academic Readiness (STAAR) in a selected northeast Texas public school. Standardized…

  10. 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,…

  11. 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…

  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. Analysis of formation pressure test results in the Mount Elbert methane hydrate reservoir through numerical simulation

    Science.gov (United States)

    Kurihara, M.; Sato, A.; Funatsu, K.; Ouchi, H.; Masuda, Y.; Narita, H.; Collett, T.S.

    2011-01-01

    Targeting the methane hydrate (MH) bearing units C and D at the Mount Elbert prospect on the Alaska North Slope, four MDT (Modular Dynamic Formation Tester) tests were conducted in February 2007. The C2 MDT test was selected for history matching simulation in the MH Simulator Code Comparison Study. Through history matching simulation, the physical and chemical properties of the unit C were adjusted, which suggested the most likely reservoir properties of this unit. Based on these properties thus tuned, the numerical models replicating "Mount Elbert C2 zone like reservoir" "PBU L-Pad like reservoir" and "PBU L-Pad down dip like reservoir" were constructed. The long term production performances of wells in these reservoirs were then forecasted assuming the MH dissociation and production by the methods of depressurization, combination of depressurization and wellbore heating, and hot water huff and puff. The predicted cumulative gas production ranges from 2.16??106m3/well to 8.22??108m3/well depending mainly on the initial temperature of the reservoir and on the production method.This paper describes the details of modeling and history matching simulation. This paper also presents the results of the examinations on the effects of reservoir properties on MH dissociation and production performances under the application of the depressurization and thermal methods. ?? 2010 Elsevier Ltd.

  14. 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.

  15. 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

  16. TankSIM: A Cryogenic Tank Performance Prediction Program

    Science.gov (United States)

    Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Moder, J. P.; Schnell, A. R.; Sutherlin, S. G.

    2015-01-01

    Developed for predicting the behavior of cryogenic liquids inside propellant tanks under various environmental and operating conditions. Provides a multi-node analysis of pressurization, ullage venting and thermodynamic venting systems (TVS) pressure control using axial jet or spray bar TVS. Allows user to combine several different phases for predicting the liquid behavior for the entire flight mission timeline or part of it. Is a NASA in-house code, based on FORTRAN 90-95 and Intel Visual FORTRAN compiler, but can be used on any other platform (Unix-Linux, Compaq Visual FORTRAN, etc.). The last Version 7, released on December 2014, included detailed User's Manual. Includes the use of several RefPROP subroutines for calculating fluid properties.

  17. Next-Term Student Performance Prediction: A Recommender Systems Approach

    OpenAIRE

    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 percent, or just half of their student populations. While there are prediction models which illuminate what factors assist with college student success, interventions that support course selections on a semester-to-semester basis have yet to be deeply understood. To further this goal, we devel...

  18. Competency-Based Model for Predicting Construction Project Managers Performance

    OpenAIRE

    Dainty, A. R. J.; Cheng, M.; Moore, D. R.

    2005-01-01

    Using behavioral competencies to influence human resource management decisions is gaining popularity in business organizations. This study identifies the core competencies associated with the construction management role and further, develops a predictive model to inform human resource selection and development decisions within large construction organizations. A range of construction managers took part in behavioral event interviews where staffs were asked to recount critical management inci...

  19. 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.

  20. Autonomous prediction of performance-based standards for heavy vehicles

    CSIR Research Space (South Africa)

    Berman, R

    2015-11-01

    Full Text Available performance-based standards approach which specifies on-road vehicle performance measures. One such standard is the low-speed swept path, which is a measure of road width required by a vehicle to complete a prescribed turning manoeuvre. This is typically...

  1. Work Ethic and Academic Performance: Predicting Citizenship and Counterproductive Behavior

    Science.gov (United States)

    Meriac, John P.

    2012-01-01

    In this study, work ethic was examined as a predictor of academic performance, compared with standardized test scores and high school grade point average (GPA). Academic performance was expanded to include student organizational citizenship behavior (OCB) and student counterproductive behavior, comprised of cheating and disengagement, in addition…

  2. Geothermal reservoir management

    Energy Technology Data Exchange (ETDEWEB)

    Scherer, C.R.; Golabi, K.

    1978-02-01

    The optimal management of a hot water geothermal reservoir was considered. The physical system investigated includes a three-dimensional aquifer from which hot water is pumped and circulated through a heat exchanger. Heat removed from the geothermal fluid is transferred to a building complex or other facility for space heating. After passing through the heat exchanger, the (now cooled) geothermal fluid is reinjected into the aquifer. This cools the reservoir at a rate predicted by an expression relating pumping rate, time, and production hole temperature. The economic model proposed in the study maximizes discounted value of energy transferred across the heat exchanger minus the discounted cost of wells, equipment, and pumping energy. The real value of energy is assumed to increase at r percent per year. A major decision variable is the production or pumping rate (which is constant over the project life). Other decision variables in this optimization are production timing, reinjection temperature, and the economic life of the reservoir at the selected pumping rate. Results show that waiting time to production and production life increases as r increases and decreases as the discount rate increases. Production rate decreases as r increases and increases as the discount rate increases. The optimal injection temperature is very close to the temperature of the steam produced on the other side of the heat exchanger, and is virtually independent of r and the discount rate. Sensitivity of the decision variables to geohydrological parameters was also investigated. Initial aquifer temperature and permeability have a major influence on these variables, although aquifer porosity is of less importance. A penalty was considered for production delay after the lease is granted.

  3. 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.

  4. Multiobjective reservoir operating rules based on cascade reservoir input variable selection method

    Science.gov (United States)

    Yang, Guang; Guo, Shenglian; Liu, Pan; Li, Liping; Xu, Chongyu

    2017-04-01

    The input variable selection in multiobjective cascade reservoir operation is an important and difficult task. To address this problem, this study proposes the cascade reservoir input variable selection (CIS) method that searches for the most valuable input variables for decision making in multiple-objectivity cascade reservoir operations. From a case study of Hanjiang cascade reservoirs in China, we derive reservoir operating rules based on the combination of CIS and Gaussian radial basis functions (RBFs) methods and optimize the rules through Pareto-archived dynamically dimensioned search (PA-DDS) with two objectives: to maximize both power generation and water supply. We select the most effective input variables and evaluate their impacts on cascade reservoir operations. From the simulated trajectories of reservoir water level, power generation, and water supply, we analyze the multiobjective operating rules with several input variables. The results demonstrate that the CIS method performs well in the selection of input variables for the cascade reservoir operation, and the RBFs method can fully express the nonlinear operating rules for cascade reservoirs. We conclude that the CIS method is an effective and stable approach to identifying the most valuable information from a large number of candidate input variables. While the reservoir storage state is the most valuable information for the Hanjiang cascade reservoir multiobjective operation, the reservoir inflow is the most effective input variable for the single-objective operation of Danjiangkou.

  5. Impact of Reservoir Operation to the Inflow Flood - a Case Study of Xinfengjiang Reservoir

    Science.gov (United States)

    Chen, L.

    2017-12-01

    Building of reservoir shall impact the runoff production and routing characteristics, and changes the flood formation. This impact, called as reservoir flood effect, could be divided into three parts, including routing effect, volume effect and peak flow effect, and must be evaluated in a whole by using hydrological model. After analyzing the reservoir flood formation, the Liuxihe Model for reservoir flood forecasting is proposed. The Xinfengjiang Reservoir is studied as a case. Results show that the routing effect makes peak flow appear 4 to 6 hours in advance, volume effect is bigger for large flood than small one, and when rainfall focus on the reservoir area, this effect also increases peak flow largely, peak flow effect makes peak flow increase 6.63% to 8.95%. Reservoir flood effect is obvious, which have significant impact to reservoir flood. If this effect is not considered in the flood forecasting model, the flood could not be forecasted accurately, particularly the peak flow. Liuxihe Model proposed for Xinfengjiang Reservoir flood forecasting has a good performance, and could be used for real-time flood forecasting of Xinfengjiang Reservoir.Key words: Reservoir flood effect, reservoir flood forecasting, physically based distributed hydrological model, Liuxihe Model, parameter optimization

  6. Reservoir Characterisation Using Wireline Evaluation And Poststack Seismic Inversion: A Lancelot Field, Southern North Sea, U.K. case study

    International Nuclear Information System (INIS)

    Mojisola, A.

    2002-01-01

    Improved reservoir characterization has been a major factor in the worldwide gain in oil recovery efficiencies over the last decades. This is because inadequate reservoir characterization, usually due to lack of appropriate tools can cause significant errors in petroleum reservoir performance prediction thereby preventing the full potential of a reservoir from being achieved. This work employs the use of wireline logs and the seismic inversion process to characterize the reservoirs in the Lancelot field. An initial reservoir analysis was carried out using the wireline evaluation. Five potential reservoirs were delineated. Thereafter reservoir parameters such as porosity, water saturation, water saturation, net-to-gross ratio of the delineated reservoirs were estimated. The seismic inversion process depends on four factors; the wavelet, the tie between the well logs and the seismic, the inversion algorithm employed and the initial model. Therefore before the main inversion, parameter tests were carried out to determine the best wavelet extraction algorithm and best inversion algorithm suited for he available data. A wavelet with a length of 70ms and a taper length of 20ms gave a close approximation of a zero phase wavelet with a stable spectrum and high dominant frequency. Based on quantitative assessment of the available inversion algorithms, the constrained blocky inversion produced the best result. Acoustic impedance, velocity and porosity sections were produced from the inverted input seismic. By incorporating geological and wireline evaluation results as constraints, the output from the inversion process were analysed. The result shows lateral variation in the reservoirs qualities of the delineated reservoirs. The seismic inversion process confirmed the Rotliegend sandstone as a prospect with a range of porosity predicted from the inversion

  7. 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

  8. 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

  9. 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

  10. 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)

  11. 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.

  12. 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.

  13. 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...

  14. Laboratory evaluation of the limitations of positive pressure safety valves on hard-shell venous reservoirs.

    Science.gov (United States)

    Almany, Daniel K; Sistino, Joseph J

    2002-06-01

    Vacuum-assisted venous drainage (VAVD) is a technique used to increase venous return during cardiopulmonary bypass (CPB). However, VAVD has created some new safety concerns. One potential problem is the pressurization of the venous reservoir in the event of vacuum failure. To prevent this overpressurization, a positive pressure release valve (PPRV) is placed on the venous reservoir. The purpose of this study was to determine if there is a difference in the pressurization of venous reservoirs using various PPRVs. The method of this study included evaluation of four different venous reservoirs and their associated PPRVs. Each reservoir was completely sealed, and two roller pumps with 1/4-in tubing were connected to the reservoir suction inlet. The roller pumps were calibrated, and a disposable pressure transducer was used to measure pressure at the venous inlet. Each reservoir was first sealed and then pressurized to test the occlusion of the roller heads. The PPRVs were tested by measuring the venous inlet pressure at a range of suction flow rates from 0-5 L/min. Linear regression analysis was performed to predict the venous inlet pressure from the rate of suction flow for each PPRV. The PPRV in the Baxter, Gish, and Gambro reservoirs maintained a low reservoir pressure (40 mmHg) even at low flow rates (1-2 L/min). It is recommended that any reservoir used for VAVD be evaluated in a similar manner to determine whether it is safe under the maximal suction and vent flow conditions possible during clinical practice.

  15. 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

  16. 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

  17. 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

  18. Cracking Tendency Prediction of High-Performance Cementitious Materials

    Directory of Open Access Journals (Sweden)

    Ke Chen

    2014-01-01

    Full Text Available The constraint ring test is widely used to assess the cracking potential for early-age cementitious materials. In this paper, the analytical expressions based on elastic mechanism are presented to estimate the residual stresses of the restrained mortar ring by considering the comprehensive effects of hydration heat, autogenous and drying shrinkage, creeping, and restraint. In the present analytical method, the stress field of the restrained ring is treated as the superposition of those caused by hydration heat, external restraint, autogenous and drying shrinkage, and creep. The factors including the properties of materials, environmental parameters such as relative humidity and temperature, the geometry effect of specimen, and the relative constraint effects of steel ring to mortar ring, are taken into account to predict the strain development with age of mortar. The temperature of the ring, the elastic modulus, the creep strain, and the split tensile strength are measured to validate the model. The age of cracking is predicted by comparing the estimated maximum tensile stress of the restrained mortar ring with the measured split tensile strength of specimen. The suitability of the present analytical method is assessed by comparing with the restraint ring test and a soundly good agreement is observed.

  19. 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...

  20. Aggregate Interview Method of ranking orthopedic applicants predicts future performance.

    Science.gov (United States)

    Geissler, Jacqueline; VanHeest, Ann; Tatman, Penny; Gioe, Terence

    2013-07-01

    This article evaluates and describes a process of ranking orthopedic applicants using what the authors term the Aggregate Interview Method. The authors hypothesized that higher-ranking applicants using this method at their institution would perform better than those ranked lower using multiple measures of resident performance. A retrospective review of 115 orthopedic residents was performed at the authors' institution. Residents were grouped into 3 categories by matching rank numbers: 1-5, 6-14, and 15 or higher. Each rank group was compared with resident performance as measured by faculty evaluations, the Orthopaedic In-Training Examination (OITE), and American Board of Orthopaedic Surgery (ABOS) test results. Residents ranked 1-5 scored significantly better on patient care, behavior, and overall competence by faculty evaluation (Porthopedic resident candidates who scored highly on the Accreditation Council for Graduate Medical Education resident core competencies as measured by faculty evaluations, performed above the national average on the OITE, and passed the ABOS part 1 examination at rates exceeding the national average. Copyright 2013, SLACK Incorporated.

  1. Could the deep squat jump predict weightlifting performance?

    Science.gov (United States)

    Vizcaya, Francisco J; Viana, Oscar; del Olmo, Miguel Fernandez; Acero, Rafael Martin

    2009-05-01

    This research was carried out with the aim of describing the deep squat jump (DSJ) and comparing it with the squat (SJ) and countermovement (CMJ) jumps, to introduce it as a strength testing tool in the monitoring and control of training in strength and power sports. Forty-eight male subjects (21 weightlifters, 12 triathletes, and 15 physical education students) performed 3 trials of DSJ, SJ, and CMJ with a 1-minute rest among them. For the weightlifters, snatch and clean and jerk results during the Spanish Championship 2004 and the 35th EU Championships 2007 were collected to study the relationship among vertical jumps and weightlifters' performance. A 1-way analysis of variance (ANOVA) showed significant differences between groups in the vertical jumps, with the highest jumps for the weightlifters and the lowest for the triathletes. An ANOVA for repeated measures (type of jump) showed better results for DSJ and CMJ than SJ in all groups. A linear regression analysis was performed to determine the association between weightlifting and vertical jump performances. Correlations among the weightlifting performance and the vertical jumps were also calculated and determined using Pearson r. Results have shown that both CMJ and DSJ are strongly correlated with weightlifting ability. Therefore, both measures can be useful for coaches as a strength testing tool in the monitoring and control of training in weightlifting.

  2. Predicting the Performance of Belt Filter Presses Using the Crown Press for Laboratory Simulation

    National Research Council Canada - National Science Library

    Graham, Todd

    1999-01-01

    .... The concept used by a BFP to achieve dewatered cake solids is relatively simple; however, replicating this performance in the laboratory in order to predict the performance of a BFP with reasonable reliability has proven to be a...

  3. 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.

  4. 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.

  5. 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.

  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. 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.

  8. 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.

  9. 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.

  10. 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.

  11. The development of a tool to predict team performance.

    Science.gov (United States)

    Sinclair, M A; Siemieniuch, C E; Haslam, R A; Henshaw, M J D C; Evans, L

    2012-01-01

    The paper describes the development of a tool to predict quantitatively the success of a team when executing a process. The tool was developed for the UK defence industry, though it may be useful in other domains. It is expected to be used by systems engineers in initial stages of systems design, when concepts are still fluid, including the structure of the team(s) which are expected to be operators within the system. It enables answers to be calculated for questions such as "What happens if I reduce team size?" and "Can I reduce the qualifications necessary to execute this process and still achieve the required level of success?". The tool has undergone verification and validation; it predicts fairly well and shows promise. An unexpected finding is that the tool creates a good a priori argument for significant attention to Human Factors Integration in systems projects. The simulations show that if a systems project takes full account of human factors integration (selection, training, process design, interaction design, culture, etc.) then the likelihood of team success will be in excess of 0.95. As the project derogates from this state, the likelihood of team success will drop as low as 0.05. If the team has good internal communications and good individuals in key roles, the likelihood of success rises towards 0.25. Even with a team comprising the best individuals, p(success) will not be greater than 0.35. It is hoped that these results will be useful for human factors professionals involved in systems design. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  12. 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.

  13. Resilience Does Not Predict Academic Performance in Gross Anatomy

    Science.gov (United States)

    Elizondo-Omana, Rodrigo Enrique; Garcia-Rodriguez, Maria de los Angeles; Hinojosa-Amaya, Jose Miguel; Villarreal-Silva, Eliud Enrique; Avilan, Rosa Ivette Guzman; Cruz, Juan Jose Bazaldua; Guzman-Lopez, Santos

    2010-01-01

    Few studies have evaluated resilience in an academic environment as it relates to academic success or failure. This work sought to assess resilience in regular and remedial students of gross anatomy during the first and second semesters of medical school and to correlate this personal trait with academic performance. Two groups of students were…

  14. 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…

  15. Sound Zones: On Performance Prediction of Contrast Control Methods

    DEFF Research Database (Denmark)

    Møller, Martin Bo; Olsen, Martin

    2016-01-01

    Low frequency personal sound zones can be created by controlling the squared sound pressure in separate spatial confined control regions. Several methods have been proposed for realizing this scenario, with different constraints and performance. Extrapolating knowledge of the resulting acoustic...... frequency sound zones are compared in an experimental study with eight woofers surrounding two control zones....

  16. 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…

  17. Diagnostic Methods for Predicting Performance Impairment Associated with Combat Stress

    Science.gov (United States)

    2007-08-01

    141 (26%) Race/Ethnicity Black/ African -American = 194 (36%) White/ Caucasian = 189 (35%) Asian = 71 (14%) Hispanic = 33 (6%) Other = 53 (9...after testing. These biosamples were analyzed for cortisol and testosterone changes that might relate to task performance or CBFv. Additional

  18. Goal Orientations Predict Academic Performance beyond Intelligence and Personality

    Science.gov (United States)

    Steinmayr, Ricarda; Bipp, Tanja; Spinath, Birgit

    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). Intelligence, the Big Five factors of personality…

  19. Expatriate career support: predicting expatriate turnover and performance

    NARCIS (Netherlands)

    J.A.V. van der Heijden (Johannes); M.L. van Engen (Marloes); J. Paauwe (Jaap)

    2009-01-01

    textabstractThis study aimed at explaining why multinational companies have difficulty retaining their repatriates as well as how multinational companies can improve in- and expatriate performance. In the study 100 in- and expatriates of a multinational company operating in the food and personal

  20. 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...

  1. Concept Inventories: Predicting the Wrong Answer May Boost Performance

    Science.gov (United States)

    Talanquer, Vincente

    2017-01-01

    Several concept inventories have been developed to elicit students' alternative conceptions in chemistry. It is suggested that heuristic reasoning may bias students' answers in these types of assessments toward intuitively appealing choices. If this is the case, one could expect students to improve their performance by engaging in more analytical…

  2. 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

  3. 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

  4. Construction of a carbonate reservoir model using pressure transient data : field case study

    Energy Technology Data Exchange (ETDEWEB)

    Taheri, S. [Petro-Iran, (Iran, Islamic Republic of); Ghanizadeh, M. [Tehran Energy, (Iran, Islamic Republic of); Haghighi, M. [Tehran Univ., (Iran, Islamic Republic of)

    2004-07-01

    Pressure transient data was integrated with other reservoir information to create a geological model of a carbonate reservoir in the Salaman offshore field in Iran. The model was created using seismic and well log data as well as the interpretation of 99 well tests performed in this field. Several features such as sealing faults, aquifer, fracturing and layering systems were observed. Two faults were identified in the northern part of the reservoir. The distance between the major fault and well number 27 was less than predicted from seismic data. An active aquifer and minor fault were also identified near well number 6. A fracture system was identified around well number 22. Most well tests showed communication between different layers of the reservoirs, suggesting interconnected layers in terms of geology. All calculated permeabilities from the well tests were found to be significantly higher than those from core analysis, suggesting that discrete fractures exist throughout the reservoir. The northern region of the reservoir has the highest permeability values and the lowest values are observed in the central part of the reservoir. 18 refs., 6 figs.

  5. 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....

  6. 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…

  7. Using the 2 x 2 Framework of Achievement Goals to Predict Achievement Emotions and Academic Performance

    Science.gov (United States)

    Putwain, David W.; Sander, Paul; Larkin, Derek

    2013-01-01

    Previous work has established how achievement emotions are related to the trichotomous model of achievement goals, and how they predict academic performance. In our study we examine relations using an additional, mastery-avoidance goal, and whether outcome-focused emotions are predicted by mastery as well as performance goals. Results showed that…

  8. Improved Fuzzy Modelling to Predict the Academic Performance of Distance Education Students

    Science.gov (United States)

    Yildiz, Osman; Bal, Abdullah; Gulsecen, Sevinc

    2013-01-01

    It is essential to predict distance education students' year-end academic performance early during the course of the semester and to take precautions using such prediction-based information. This will, in particular, help enhance their academic performance and, therefore, improve the overall educational quality. The present study was on the…

  9. Numerical study of sediment and137Cs discharge out of reservoirs during various scale rainfall events.

    Science.gov (United States)

    Kurikami, Hiroshi; Funaki, Hironori; Malins, Alex; Kitamura, Akihiro; Onishi, Yasuo

    2016-11-01

    Contamination of reservoirs with radiocesium is one of the main concerns in Fukushima Prefecture, Japan. We performed simulations using the three-dimensional finite volume code FLESCOT to understand sediment and radiocesium transport in generic models of reservoirs with parameters similar to those in Fukushima Prefecture. The simulations model turbulent water flows, transport of sediments with different grain sizes, and radiocesium migration both in dissolved and particulate forms. To demonstrate the validity of the modeling approach for the Fukushima environment, we performed a test simulation of the Ogaki Dam reservoir over Typhoon Man-yi in September 2013 and compared the results with field measurements. We simulated a set of generic model reservoirs systematically varying features such as flood intensity, reservoir volume and the radiocesium distribution coefficient. The results ascertain how these features affect the amount of sediment or 137 Cs discharge downstream from the reservoirs, and the forms in which 137 Cs is discharged. Silt carries the majority of the radiocesium in the larger flood events, while the clay-sorbed followed by dissolved forms are dominant in smaller events. The results can be used to derive indicative values of discharges from Fukushima reservoirs under arbitrary flood events. For example the generic model simulations indicate that about 30% of radiocesium that entered the Ogaki Dam reservoir over the flood in September 2015 caused by Typhoon Etau discharged downstream. Continued monitoring and numerical predictions are necessary to quantify future radiocesium migration in Fukushima Prefecture and evaluate possible countermeasures since reservoirs can be a sink of radiocesium. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. An efficient approach to understanding and predicting the effects of multiple task characteristics on performance.

    Science.gov (United States)

    Richardson, Miles

    2017-04-01

    In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.

  11. Prediction of Job Performance: Review of Military Studies

    Science.gov (United States)

    1982-03-01

    Thorndike, 1949; Wherry, 1950). Guion (1978) has noted that job requirements 2There is fairly universal agreement today that job performance is complex and...34 Guion (1967, 1976) described a variety of uses of the term since then. variables used for population definition and control; variables that correlate...Development Command, August 1960. Brown, G. H., & Vineberg, R. A follow-up study of experimentally and conventionally trained field radio repairmen (HumRRO Te h

  12. Fluid reasoning predicts future mathematical performance among children and adolescents.

    Science.gov (United States)

    Green, Chloe T; Bunge, Silvia A; Briones Chiongbian, Victoria; Barrow, Maia; Ferrer, Emilio

    2017-05-01

    The aim of this longitudinal study was to determine whether fluid reasoning (FR) plays a significant role in the acquisition of mathematics skills above and beyond the effects of other cognitive and numerical abilities. Using a longitudinal cohort sequential design, we examined how FR measured at three assessment occasions, spaced approximately 1.5years apart, predicted math outcomes for a group of 69 participants between ages 6 and 21years across all three assessment occasions. We used structural equation modeling (SEM) to examine the direct and indirect relations between children's previous cognitive abilities and their future math achievement. A model including age, FR, vocabulary, and spatial skills accounted for 90% of the variance in future math achievement. In this model, FR was the only significant predictor of future math achievement; age, vocabulary, and spatial skills were not significant predictors. Thus, FR was the only predictor of future math achievement across a wide age range that spanned primary school and secondary school. These findings build on Cattell's conceptualization of FR as a scaffold for learning, showing that this domain-general ability supports the acquisition of rudimentary math skills as well as the ability to solve more complex mathematical problems. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Impact of environmental factors on maintaining water quality of Bakreswar reservoir, India

    Directory of Open Access Journals (Sweden)

    Moitreyee Banerjee

    2015-09-01

    Full Text Available Reservoirs and dams are engineered systems designed to serve purposes like supply of drinking water as well as other commercial and industrial use. A thorough assessment of water quality for these systems is thus necessary. The present study is carried out at Bakreswar reservoir, in Birbhum district, which was created by the dam, built on Bakreswar River. The major purpose of the reservoir is the supply of drinking water to the surrounding villages and Bakreswar Thermal Power Station. Water samples were collected fortnightly from three different stations of the reservoir. Physical and chemical factors like dissolved oxygen, atmospheric temperature, pH, conductivity, salinity, solar radiation, water temperature, alkalinity, hardness, chloride, productivity etc. were analysed using standard procedure. Abundance data is calculated for four major groups of zooplanktons (Cladocera, Copepoda, Ostracoda, and Rotifera with the software PAST 2.1. Multivariate statistical analysis like PCA, hierarchical cluster and CCA are performed in order to predict the temporal variation in the water quality factors using SPSS 20. Distinct seasonal variation was found for environmental factors and zooplankton groups. Bakreswar reservoir has good assemblage of zooplankton and distinct temporal variation of environmental factors and its association with zooplankton predicts water quality condition. These results could help in formulating proper strategies for advanced water quality management and conservation of reservoir ecosystem. Key elements for growth and sustenance of the system can then be evaluated and this knowledge can be further applied for management purposes.

  14. 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....

  15. 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…

  16. Stream, Lake, and Reservoir Management.

    Science.gov (United States)

    Dai, Jingjing; Mei, Ying; Chang, Chein-Chi

    2017-10-01

    This review on stream, lake, and reservoir management covers selected 2016 publications on the focus of the following sections: Stream, lake, and reservoir management • Water quality of stream, lake, and reservoirReservoir operations • Models of stream, lake, and reservoir • Remediation and restoration of stream, lake, and reservoir • Biota of stream, lake, and reservoir • Climate effect of stream, lake, and reservoir.

  17. Allometric scaling and predicting cycling performance in (well-) trained female cyclists.

    Science.gov (United States)

    Lamberts, R P; Davidowitz, K J

    2014-03-01

    As female cycling attains greater professionalism, a larger emphasis is placed on the ability to predict and monitor changes in their cycling performance. The main aim of this study was to determine if peak power output (PPO) adjusted for body mass (W · kg-0.32) accurately predicts flat 40-km time trial performance (40 km TT) in female cyclists as found in men. 20 (well-) trained female cyclists completed a PPO test including maximal oxygen consumption (VO2max) and a flat 40 km TT test. Relationships between cycling performance parameters were also compared to the cycling performance of 45 male cyclists. Allometrically scaled PPW (W · kg(-0.32)) most accurately predicted 40 km TT performance in the female cyclists (r = -0.87, pequations should be used when predicting relative cycling performance parameters. © Georg Thieme Verlag KG Stuttgart · New York.

  18. 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.

  19. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    Energy Technology Data Exchange (ETDEWEB)

    Shibata, H., E-mail: shibata@daedalus.k.u-tokyo.ac.jp; Watanabe, Y. [Department of Aeronautics and Astronautics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Suzuki, K. [Department of Advanced Energy, The University of Tokyo, Kashiwanoha, Kashiwa, Chiba 277-8561 (Japan)

    2016-05-15

    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.

  20. 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

  1. Status of Wheeler Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    1990-09-01

    This is one in a series of status reports prepared by the Tennessee Valley Authority (TVA) for those interested in the conditions of TVA reservoirs. This overview of Wheeler Reservoir summarizes reservoir purposes and operation, reservoir and watershed characteristics, reservoir uses and use impairments, and water quality and aquatic biological conditions. The information presented here is from the most recent reports, publications, and original data available. If no recent data were available, historical data were summarized. If data were completely lacking, environmental professionals with special knowledge of the resource were interviewed. 12 refs., 2 figs.

  2. 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

  3. Observed and predicted performance of the global IMS infrasound network

    Science.gov (United States)

    Le Pichon, A.; Ceranna, L.; Landes, M.

    2012-04-01

    The International Monitoring System (IMS) infrasound network is being deployed to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Global-scale analyses of data recorded by this network indicate that the detection capability exhibits strong spatio-temporal variations. Previous studies estimated radiated acoustic source energy from remote infrasound observations using empirical yield-scaling relations, which account for the along-path stratospheric winds. Although the empirical wind correction reduces the variance in the explosive energy versus pressure relationship, large error remains in the yield estimates. Numerical modeling techniques are now widely employed to investigate the role of different factors describing atmospheric infrasound sources and propagation. Here we develop a theoretical attenuation relation from a large set of numerical simulations using the Parabolic Equation method. This relation accounts for the effects of the source frequency; geometrical spreading and dissipation; and realistic atmospheric specifications on the pressure wave attenuation. Compared with previous studies, the derived attenuation relation incorporates a more realistic physical description of infrasound propagation. By incorporating real ambient noise information at the receivers, we obtain the minimum detectable source amplitude in the frequency band of interest for detecting explosions. Empirical relations between the source spectrum and explosion yield are used to infer detection thresholds in tons of TNT equivalent. In the context of future verification of the CTBT, the obtained attenuation relation provides a more realistic picture of the spatio-temporal variability of the IMS network performance. The attenuation relation could also be used in the design and maintenance of an arbitrary infrasound monitoring network.

  4. 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

    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...... benchmark dataset from 2009 with prediction performances generated on data subsequently added to the Immune Epitope Database (IEDB) which served as a blind set. Results: We found that cross-validated performances systematically overestimated performance on the blind set. This was found not to be due...... to the presence of similar peptides in the cross-validation dataset. Rather, we found that small size and low sequence/affinity diversity of either training or blind datasets were associated with large differences in cross-validated vs. blind prediction performances. We use these findings to derive quantitative...

  5. 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.

  6. Reservoir-induced seismicity at Castanhao reservoir, NE Brazil

    Science.gov (United States)

    Nunes, B.; do Nascimento, A.; Ferreira, J.; Bezerra, F.

    2012-04-01

    Our case study - the Castanhão reservoir - is located in NE Brazil on crystalline rock at the Borborema Province. The Borborema Province is a major Proterozoic-Archean terrain formed as a consequence of convergence and collision of the São Luis-West Africa craton and the São Francisco-Congo-Kasai cratons. This reservoir is a 60 m high earth-filled dam, which can store up to 4.5 billion m3 of water. The construction begun in 1990 and finished in October 2003.The first identified reservoir-induced events occurred in 2003, when the water level was still low. The water reached the spillway for the first time in January 2004 and, after that, an increase in seismicity occured. The present study shows the results of a campaign done in the period from November 19th, 2009 to December 31th, 2010 at the Castanhão reservoir. We deployed six three-component digital seismographic station network around one of the areas of the reservoir. We analyzed a total of 77 events which were recorded in at least four stations. To determine hypocenters and time origin, we used HYPO71 program (Lee & Lahr, 1975) assuming a half-space model with following parameters: VP= 5.95 km/s and VP/VS=1.73. We also performed a relocation of these events using HYPODD (Waldhauser & Ellsworth, 2000) programme. The input data used we used were catalogue data, with all absolute times. The results from the spatio-temporal suggest that different clusters at different areas and depths are triggered at different times due to a mixture of: i - pore pressure increase due to diffusion and ii - increase of pore pressure due to the reservoir load.

  7. 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.

  8. 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.

  9. 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.

  10. Pre-Clinical Grades Predict Clinical Performance in the MBBS Stage ...

    African Journals Online (AJOL)

    olayemitoyin

    Summary: In the preclinical sciences, statistically significant predictive values have been reported between the performances in one discipline and the others, supporting the hypothesis that students who perform well in one discipline were likely to perform well in the other disciplines. We therefore decided to conduct a ...

  11. 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.

  12. The impact of sequence length and number of sequences on promoter prediction performance.

    Science.gov (United States)

    Carvalho, Sávio G; Guerra-Sá, Renata; de C Merschmann, Luiz H

    2015-01-01

    The advent of rapid evolution on sequencing capacity of new genomes has evidenced the need for data analysis automation aiming at speeding up the genomic annotation process and reducing its cost. Given that one important step for functional genomic annotation is the promoter identification, several studies have been taken in order to propose computational approaches to predict promoters. Different classifiers and characteristics of the promoter sequences have been used to deal with this prediction problem. However, several works in literature have addressed the promoter prediction problem using datasets containing sequences of 250 nucleotides or more. As the sequence length defines the amount of dataset attributes, even considering a limited number of properties to characterize the sequences, datasets with a high number of attributes are generated for training classifiers. Once high-dimensional datasets can degrade the classifiers predictive performance or even require an infeasible processing time, predicting promoters by training classifiers from datasets with a reduced number of attributes, it is essential to obtain good predictive performance with low computational cost. To the best of our knowledge, there is no work in literature that verified in a systematic way the relation between the sequences length and the predictive performance of classifiers. Thus, in this work, we have evaluated the impact of sequence length variation and training dataset size (number of sequences) on the predictive performance of classifiers. We have built sixteen datasets composed of different sized sequences (ranging in length from 12 to 301 nucleotides) and evaluated them using the SVM, Random Forest and k-NN classifiers. The best predictive performances reached by SVM and Random Forest remained relatively stable for datasets composed of sequences varying in length from 301 to 41 nucleotides, while k-NN achieved its best performance for the dataset composed of 101 nucleotides. We

  13. Does the medical college admission test predict global academic performance in osteopathic medical school?

    Science.gov (United States)

    Evans, Paul; Wen, Frances K

    2007-04-01

    To investigate the extent to which Medical College Admission Test (MCAT) subscores predict the overall academic performance of osteopathic medical students. We examined the value of MCAT subscores in predicting students' global academic performance in osteopathic medical school, as defined by grade point average in basic science (basic GPA), clinical instruction (clinical GPA), cumulative grade point average (total GPA), and national licensing examination scores on the Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) Level 1 and Level 2. Subjects were 434 osteopathic medical students of the Oklahoma State University College of Osteopathic Medicine in Tulsa who either graduated or were expected to graduate between the years 1999 and 2003. Standard, multivariate linear regression analyses were conducted for each of the five performance variables to assess the relative importance of MCAT subtest scores and cumulative undergraduate GPA (total UGPA) in predicting academic performance. Total UGPA was the most important, significant predictor (beta=.13-.33) in overall student academic performance for all five analyzed variables. Less predictive of overall academic performance (beta=-.01-.21) were MCAT subcores. However, the MCAT biological sciences subscore was a significant predictor of basic GPA (beta=.14), the MCAT physical sciences subscore significantly predicted COMLEX-USA Level 1 scores (beta=.15), and the MCAT verbal reasoning subscore significantly predicted COMLEX-USA Level 2 scores (beta=.21). The subscore for the MCAT writing sample was not a significant predictor of overall academic performance. Total undergraduate GPA had the highest predictive value for academic performance as measured by basic GPA, clinical GPA, total GPA, and COMLEX-USA Level 1 and Level 2 scores. The present study found MCAT subscores to be of limited predictive value in determining global academic performance.

  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. 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.

  16. 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.

  17. 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.…

  18. Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

    Science.gov (United States)

    Lee, Young-Jin

    2015-01-01

    This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

  19. Predicting human performance differences on multiple interface alternatives: KLM, GOMS and CogTool are unreliable

    NARCIS (Netherlands)

    Jorritsma, Wiard; Haga, Peter-Jan; Cnossen, Fokie; Dierckx, Rudi; Oudkerk, Matthijs; van Ooijen, Peter

    2015-01-01

    Cognitive modeling tools, such as KLM, GOMS and CogTool, can be used to predict human performance on interface designs before they are implemented and without the need for user testing. The model predictions can inform interface design, because they allow designers to quantitatively compare multiple

  20. 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…

  1. 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…

  2. 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 (pperformance 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.

  3. 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

  4. 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

    Political skill is a social effectiveness construct with a demonstrated capacity to predict job performance. However, because performance prediction research in this area to date has made exclusive use of self-reports of political skill, and due to frequent distrust of self-ratings of constructs......-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...... in important personnel decisions, there is a need to investigate how multiple alternative sources of political skill and job performance measures relate, thus raising both theoretical and methodological issues. In three studies, employing a triadic data collection methodology, and utilising both cross...

  5. 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

  6. 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...

  7. In vitro models for the prediction of in vivo performance of oral dosage forms

    DEFF Research Database (Denmark)

    Kostewicz, Edmund S; Abrahamsson, Bertil; Brewster, Marcus

    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 connectio...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Determination of lower and upper bounds of predicted production from history-matched models

    NARCIS (Netherlands)

    van Essen, G. M.; Kahrobaei, S.S.; van Oeveren, H.; van den Hof, P.M.J.; Jansen, J.D.

    2016-01-01

    We present a method to determine lower and upper bounds to the predicted production or any other economic objective from history-matched reservoir models. The method consists of two steps: 1) performing a traditional computer-assisted history match of a reservoir model with the objective to

  13. Analysis on fuel thermal conductivity model of the computer code for performance prediction of fuel rods

    International Nuclear Information System (INIS)

    Li Hai; Huang Chen; Du Aibing; Xu Baoyu

    2014-01-01

    The thermal conductivity is one of the most important parameters in the computer code for performance prediction for fuel rods. Several fuel thermal conductivity models used in foreign computer code, including thermal conductivity models for MOX fuel and UO 2 fuel were introduced in this paper. Thermal conductivities were calculated by using these models, and the results were compared and analyzed. Finally, the thermal conductivity model for the native computer code for performance prediction for fuel rods in fast reactor was recommended. (authors)

  14. Biological lifestyle factors in adult distance education: predicting cognitive and learning performance

    OpenAIRE

    Gijselaers, Jérôme

    2015-01-01

    The aim of this dissertation was to explore the characteristics of different student groups (i.e., successful, non-successful, and non-starting). The second aim was to examine whether biological lifestyle factors (e.g. physical activity, sleep, and nutrition) predicted learning performance. Third, it aimed to investigate whether these biological lifestyle factors predicted cognitive performance, as this can be a predictor for learning in traditional education. The final aim was to determine w...

  15. Reactive Tracers for Characterizing Fractured Geothermal Reservoirs

    Science.gov (United States)

    Hawkins, Adam J.

    Multi-component tracer tests were conducted at a 10 x 10 m well field located in the Altona Flat Rocks of northern New York. Temperature advancement between two wells separated by 14 m was monitored throughout the well field during progressive heating of the reservoir over 6 d. Multiple approaches to predicting heat transport were applied to field data and compared to temperature rise recorded during reservoir heat-up. Tracer analysis incorporated both an analytical one-dimensional model and a two-dimensional numerical model for non-uniform fractures experiencing "flow-channeling." Modeling efforts demonstrated that estimating heat transfer surface area using a combined inert/adsorbing tracer (cesium-iodide) could provide accurate forecasting of premature thermal breakthrough. In addition, thermally degrading tracer tests were used to monitor inter-well temperature during progressive reservoir heating. Inert tracers alone were, in general, inadequate in forecasting thermal performance. In fact, moment analysis shows that, mathematically, thermal breakthrough is independent of parameters that primarily influence inert tracers. The most accurate prediction of thermal breakthrough using inert tracer alone was produced by treating hydrodynamic dispersion as a truly Fickian process with known and accurate mathematical models. Under this assumption, inert tracer data was matched by solving an inverse problem for non-uniform fracture aperture. Early arrival of the thermal front was predicted at the production, but was less accurate than using a combined inert/adsorbing tracer test. The spatial distribution of fluid flow paths in the plane of the fracture were identified using computational models, Fiber-Optic Distributed Temperature Sensing (FO-DTS), and Ground Penetrating Radar (GPR) imaging of saline tracer flow paths in the target fracture. Without exception, fluid flow was found to be concentrated in a roughly 1 m wide flow channel directly between the two wells. The

  16. 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

  17. 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.

  18. Does performance on school-administered mock boards predict performance on a dental licensure exam?

    Science.gov (United States)

    Stewart, Carol M; Bates, Robert E; Smith, Gregory E

    2004-04-01

    Many dental schools consider the successful completion of a state or regional dental licensure examination as one of the significant benchmarks for assessing effectiveness of the curriculum. At the University of Florida College of Dentistry (UFCD), performance on the state dental licensure examination is monitored and compared with senior year mock board performance and clinical productivity to identify factors that may contribute to state board "pass" rates. A retrospective analysis was conducted of "first-time" performance on the Florida Dental Licensure Exam for graduates from classes 1996 to 2003. Using ANOVA, licensure exam performance data was analyzed and compared with performance on the senior mock board exam and clinical productivity, determined by numbers of procedures completed in each discipline. Significant relationships were noted between four of thirteen aspects of mock board performance and clinical productivity data and performance on the Florida Dental Licensure Exam. First, a significant relationship (pplaning) and performance on the like procedures on the licensure exam. Likewise, no significance was found between the remaining four productivity measures (numbers of Class II composites, endodontic teeth treated, crowns and abutments completed, and quadrants of periodontal scaling/root planing) and performance of these procedures on the state licensure exam.

  19. 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.

  20. A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms.

    Science.gov (United States)

    Lai, Fu-Jou; Chang, Hong-Tsun; Huang, Yueh-Min; Wu, Wei-Sheng

    2014-01-01

    Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to measure the performance of new

  1. Assessing the performance of prediction models: a framework for traditional and novel measures

    DEFF Research Database (Denmark)

    Steyerberg, Ewout W; Vickers, Andrew J; Cook, Nancy R

    2010-01-01

    (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation...... be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor...... of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always...

  2. Electromagnetic Heating Methods for Heavy Oil Reservoirs

    International Nuclear Information System (INIS)

    Sahni, A.; Kumar, M.; Knapp, R.B.

    2000-01-01

    The most widely used method of thermal oil recovery is by injecting steam into the reservoir. A well-designed steam injection project is very efficient in recovering oil, however its applicability is limited in many situations. Simulation studies and field experience has shown that for low injectivity reservoirs, small thickness of the oil-bearing zone, and reservoir heterogeneity limits the performance of steam injection. This paper discusses alternative methods of transferring heat to heavy oil reservoirs, based on electromagnetic energy. They present a detailed analysis of low frequency electric resistive (ohmic) heating and higher frequency electromagnetic heating (radio and microwave frequency). They show the applicability of electromagnetic heating in two example reservoirs. The first reservoir model has thin sand zones separated by impermeable shale layers, and very viscous oil. They model preheating the reservoir with low frequency current using two horizontal electrodes, before injecting steam. The second reservoir model has very low permeability and moderately viscous oil. In this case they use a high frequency microwave antenna located near the producing well as the heat source. Simulation results presented in this paper show that in some cases, electromagnetic heating may be a good alternative to steam injection or maybe used in combination with steam to improve heavy oil production. They identify the parameters which are critical in electromagnetic heating. They also discuss past field applications of electromagnetic heating including technical challenges and limitations

  3. Deep Recurrent Model for Server Load and Performance Prediction in Data Center

    Directory of Open Access Journals (Sweden)

    Zheng Huang

    2017-01-01

    Full Text Available Recurrent neural network (RNN has been widely applied to many sequential tagging tasks such as natural language process (NLP and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory (LSTM units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events (user requests, which is the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center.

  4. Episodic entrainment of primordial material in plumes from isolated lower mantle reservoirs

    Science.gov (United States)

    Williams, C. D.; McNamara, A. K.; Garnero, E. J.; Van Soest, M. C.

    2012-12-01

    The noble gas systematics observed in ocean island basalts (OIBs) relative to mid-ocean ridge basalts (MORBs), suggests OIBs preferentially sample a primordial reservoir located somewhere within Earth's mantle. The lower mantle has been favored as a candidate reservoir, either in its entirety or discrete reservoirs located within it. Thermal plumes originating from the lower mantle could potentially sample these reservoirs, which may have remained isolated from the MORB source region over much of Earth's history. Recently, seismic observations of two, nearly anti-podal large, low-shear velocity provinces (LLSVPs) in the lowermost mantle have been hypothesized as being chemically distinct, and thus, may be long-lived reservoirs that have retained primordial noble gas signatures from earlier in Earth's history. Geodynamic models predict that thermal plumes are likely to be associated with LLSVPs and could potentially entrain a small amount of these chemically distinct reservoirs, which may ultimately reach the surface of the Earth in the form of OIBs. However, isotopic variability within OIBs challenges the notion of multiple plumes tapping the same reservoir. Here, we perform geodynamic calculations that investigate the time-dependent rate of material entrained into thermal plumes from these primordial reservoirs. In particular, we examine how the rate of entrainment varies within a single, long-lived thermal plume with a relatively steady buoyancy flux. Using phase relations for mantle peridotite, the amount of entrained material comprising the melt is estimated. We find that time-dependent dynamical processes at the interface between a deep, primordial reservoir and the base of a mantle plume strongly influences the entrainment rate, causing the amount of entrainment to vary episodically with time. Thus, melts rising to the surface (e.g., OIBs) are predicted to contain variable proportions of material entrained from these primordial reservoirs. This time

  5. Using Chemicals to Optimize Conformance Control in Fractured Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Liu, Jin; Wavrik, Kathryn

    1999-09-27

    This report describes work performed during the first year of the project, ''Using Chemicals to Optimize Conformance Control in Fractured Reservoirs.'' This research project has three objectives. The first objective is 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 is to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective is to develop procedures to optimize blocking agent placement in naturally fractured reservoirs. This research project consists of three tasks, each of which addresses one of the above objectives. Our work is directed at both injection wells and production wells and at vertical, horizontal, and highly deviated wells.

  6. Performance predictions for mechanical excavators in Yucca Mountain tuffs; Yucca Mountain Site Characterization Project

    Energy Technology Data Exchange (ETDEWEB)

    Ozdemir, L.; Gertsch, L.; Neil, D.; Friant, J. [Colorado School of Mines, Golden, CO (United States). Earth Mechanics Inst.

    1992-09-01

    The performances of several mechanical excavators are predicted for use in the tuffs at Yucca Mountain: Tunnel boring machines, the Mobile Miner, a roadheader, a blind shaft borer, a vertical wheel shaft boring machine, raise drills, and V-Moles. Work summarized is comprised of three parts: Initial prediction using existing rock physical property information; Measurement of additional rock physical properties; and Revision of the initial predictions using the enhanced database. The performance predictions are based on theoretical and empirical relationships between rock properties and the forces-experienced by rock cutters and bits during excavation. Machine backup systems and excavation design aspects, such as curves and grades, are considered in determining excavator utilization factors. Instanteous penetration rate, advance rate, and cutter costs are the fundamental performance indicators.

  7. 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.

  8. Results of high resolution seismic imaging experiments for defining permeable pathways in fractured gas reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Majer, E.L.; Peterson, J.E.; Daley, T. [and others

    1997-10-01

    As part of its Department of Energy (DOE) Industry cooperative program in oil and gas, Berkeley Lab has an ongoing effort in cooperation with Industry partners to develop equipment, field techniques, and interpretational methods to further the practice of characterizing fractured heterogeneous reservoirs. The goal of this work is to demonstrate the combined use of state-of-the-art technology in fluid flow modeling and geophysical imaging into an interdisciplinary approach for predicting the behavior of heterogeneous fractured gas reservoirs. The efforts in this program have mainly focused on using seismic methods linked with geologic and reservoir engineering analysis for the detection and characterization of fracture systems in tight gas formations, i.e., where and how to detect the fractures, what are the characteristics of the fractures, and how the fractures interact with the natural stresses, lithology, and their effect on reservoir performance. The project has also integrated advanced reservoir engineering methods for analyzing flow in fractured systems such that reservoir management strategies can be optimized. The work at Berkeley Lab focuses on integrating high resolution seismic imaging, (VSP, crosswell, and single well imaging), geologic information and well test data to invert for flow paths in fractured systems.

  9. Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance.

    Science.gov (United States)

    Eksborg, Staffan

    2013-01-01

    Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis. Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal. The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis. The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8-1.2.

  10. 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.

  11. Stochastic Reservoir Characterization Constrained by Seismic Data

    Energy Technology Data Exchange (ETDEWEB)

    Eide, Alfhild Lien

    1999-07-01

    In order to predict future production of oil and gas from a petroleum reservoir, it is important to have a good description of the reservoir in terms of geometry and physical parameters. This description is used as input to large numerical models for the fluid flow in the reservoir. With increased quality of seismic data, it is becoming possible to extend their use from the study of large geologic structures such as seismic horizons to characterization of the properties of the reservoir between the horizons. Uncertainties because of the low resolution of seismic data can be successfully handled by means of stochastic modeling, and spatial statistics can provide tools for interpolation and simulation of reservoir properties not completely resolved by seismic data. This thesis deals with stochastic reservoir modeling conditioned to seismic data and well data. Part I presents a new model for stochastic reservoir characterization conditioned to seismic traces. Part II deals with stochastic simulation of high resolution impedance conditioned to measured impedance. Part III develops a new stochastic model for calcite cemented objects in a sandstone background; it is a superposition of a marked point model for the calcites and a continuous model for the background.

  12. The better model to predict and improve pediatric health care quality: performance or importance-performance?

    Science.gov (United States)

    Olsen, Rebecca M; Bryant, Carol A; McDermott, Robert J; Ortinau, David

    2013-01-01

    The perpetual search for ways to improve pediatric health care quality has resulted in a multitude of assessments and strategies; however, there is little research evidence as to their conditions for maximum effectiveness. A major reason for the lack of evaluation research and successful quality improvement initiatives is the methodological challenge of measuring quality from the parent perspective. Comparison of performance-only and importance-performance models was done to determine the better predictor of pediatric health care quality and more successful method for improving the quality of care provided to children. Fourteen pediatric health care centers serving approximately 250,000 patients in 70,000 households in three West Central Florida counties were studied. A cross-sectional design was used to determine the importance and performance of 50 pediatric health care attributes and four global assessments of pediatric health care quality. Exploratory factor analysis revealed five dimensions of care (physician care, access, customer service, timeliness of services, and health care facility). Hierarchical multiple regression compared the performance-only and the importance-performance models. In-depth interviews, participant observations, and a direct cognitive structural analysis identified 50 health care attributes included in a mailed survey to parents(n = 1,030). The tailored design method guided survey development and data collection. The importance-performance multiplicative additive model was a better predictor of pediatric health care quality. Attribute importance moderates performance and quality, making the importance-performance model superior for measuring and providing a deeper understanding of pediatric health care quality and a better method for improving the quality of care provided to children. Regardless of attribute performance, if the level of attribute importance is not taken into consideration, health care organizations may spend valuable

  13. Predicting performance and performance satisfaction: mindfulness and beliefs about the ability to deal with social barriers in sport.

    Science.gov (United States)

    Blecharz, Jan; Luszczynska, Aleksandra; Scholz, Urte; Schwarzer, Ralf; Siekanska, Malgorzata; Cieslak, Roman

    2014-05-01

    This research investigates the role of beliefs about the ability to deal with specific social barriers and its relationships to mindfulness, football performance, and satisfaction with one's own and team performance. Study 1 aimed at eliciting these social barriers. Study 2 tested (i) whether self-efficacy referring to social barriers would predict performance over and above task-related self-efficacy and collective efficacy and (ii) the mediating role of self-efficacy to overcome social barriers in the relationship between mindfulness and performance. Participants were football (soccer) players aged 16-21 years (Study 1: N=30; Study 2: N=101, longitudinal sample: n=88). Study 1 resulted in eliciting 82 social barriers referring to team, peer leadership, and coaches. Study 2 showed that task-related self-efficacy and collective efficacy explained performance satisfaction at seven-month follow-up, whereas self-efficacy referring to social barriers explained shooting performance at seven-month follow-up. Indirect associations between mindfulness and performance were found with three types of self-efficacy referring to social barriers, operating as parallel mediators. Results provide evidence for the role of beliefs about the ability to cope with social barriers and show a complex interplay between different types of self-efficacy and collective efficacy in predicting team sport performance.

  14. Prediction of intrinsic motivation and sports performance using 2 x 2 achievement goal framework.

    Science.gov (United States)

    Li, Chiung-Huang; Chi, Likang; Yeh, Suh-Ruu; Guo, Kwei-Bin; Ou, Cheng-Tsung; Kao, Chun-Chieh

    2011-04-01

    The purpose of this study was to examine the influence of 2 x 2 achievement goals on intrinsic motivation and performance in handball. Participants were 164 high school athletes. All completed the 2 x 2 Achievement Goals Questionnaire for Sport and the Intrinsic Motivation subscale of the Sport Motivation Scale; the coach for each team rated his athletes' overall sports performance. Using simultaneous-regression analyses, mastery-approach goals positively predicted both intrinsic motivation and performance in sports, whereas performance-avoidance goals negatively predicted sports performance. These results suggest that athletes who pursue task mastery and improvement of their competence perform well and enjoy their participation. In contrast, those who focus on avoiding normative incompetence perform poorly.

  15. Predicting failing performance on a standardized patient clinical performance examination: the importance of communication and professionalism skills deficits.

    Science.gov (United States)

    Chang, Anna; Boscardin, Christy; Chou, Calvin L; Loeser, Helen; Hauer, Karen E

    2009-10-01

    The purpose is to determine which assessment measures identify medical students at risk of failing a clinical performance examination (CPX). Retrospective case-control, multiyear design, contingency table analysis, n = 149. We identified two predictors of CPX failure in patient-physician interaction skills: low clerkship ratings (odds ratio 1.79, P = .008) and student progress review for communication or professionalism concerns (odds ratio 2.64, P = .002). No assessments predicted CPX failure in clinical skills. Performance concerns in communication and professionalism identify students at risk of failing the patient-physician interaction portion of a CPX. This correlation suggests that both faculty and standardized patients can detect noncognitive traits predictive of failing performance. Early identification of these students may allow for development of a structured supplemental curriculum with increased opportunities for practice and feedback. The lack of predictors in the clinical skills portion suggests limited faculty observation or feedback.

  16. Performance of local information-based link prediction: a sampling perspective

    Science.gov (United States)

    Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

    2012-08-01

    Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

  17. In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models.

    Science.gov (United States)

    Sjögren, Erik; Thörn, Helena; Tannergren, Christer

    2016-06-06

    Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and

  18. The Prediction of College Student Academic Performance and Retention: Application of Expectancy and Goal Setting Theories

    Science.gov (United States)

    Friedman, Barry A.; Mandel, Rhonda G.

    2010-01-01

    Student retention and performance in higher education are important issues for educators, students, and the nation facing critical professional labor shortages. Expectancy and goal setting theories were used to predict academic performance and college student retention. Students' academic expectancy motivation at the start of the college…

  19. A Cross-Validation Study of Police Recruit Performance as Predicted by the IPI and MMPI.

    Science.gov (United States)

    Shusman, Elizabeth J.; And Others

    Validation and cross-validation studies were conducted using the Minnesota Multiphasic Personality Inventory (MMPI) and Inwald Personality Inventory (IPI) to predict job performance for 698 urban male police officers who completed a six-month training academy. Job performance criteria evaluated included absence, lateness, derelictions, negative…

  20. Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

    Science.gov (United States)

    Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

    2011-01-01

    In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

  1. The Role of Resilience, Delayed Gratification and Stress in Predicting Academic Performance

    Science.gov (United States)

    Cheng, Vivienne; Catling, Jonathan

    2015-01-01

    Transition to university is an important and potentially stressful life event for students. Previous studies have shown that resilience, delay of gratification and stress can affect the academic performance of students. However, none have shown the effect of these factors in predicting academic performance, hence the current study aimed to look at…

  2. A predictive model of flight crew performance in automated air traffic control and flight management operations

    Science.gov (United States)

    1995-01-01

    Prepared ca. 1995. This paper describes Air-MIDAS, a model of pilot performance in interaction with varied levels of automation in flight management operations. The model was used to predict the performance of a two person flight crew responding to c...

  3. Assessing the performance of prediction models: A framework for traditional and novel measures

    NARCIS (Netherlands)

    E.W. Steyerberg (Ewout); A.J. Vickers (Andrew); N.R. Cook (Nancy); T.A. Gerds (Thomas); M. Gonen (Mithat); N. Obuchowski (Nancy); M. Pencina (Michael); M.W. Kattan (Michael)

    2010-01-01

    textabstractThe performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the

  4. Predicting Arithmetical Achievement from Neuro-Psychological Performance: A Longitudinal Study.

    Science.gov (United States)

    Fayol, Michel; Barrouillet, Pierre; Marinthe, Catherine

    1998-01-01

    Assessed whether performances of 5- and 6-year olds in arithmetic tests can be predicted from their performances in neuropsychological tests. Participants completed neuropsychological, drawing, and arithmetic tests at 5 and 6 years of age. Findings at older age were correctly assumed by conclusions of first evaluation. (LBT)

  5. Stata Modules for Calculating Novel Predictive Performance Indices for Logistic Models.

    Science.gov (United States)

    Barkhordari, Mahnaz; Padyab, Mojgan; Hadaegh, Farzad; Azizi, Fereidoun; Bozorgmanesh, Mohammadreza

    2016-01-01

    Prediction is a fundamental part of prevention of cardiovascular diseases (CVD). The development of prediction algorithms based on the multivariate regression models loomed several decades ago. Parallel with predictive models development, biomarker researches emerged in an impressively great scale. The key question is how best to assess and quantify the improvement in risk prediction offered by new biomarkers or more basically how to assess the performance of a risk prediction model. Discrimination, calibration, and added predictive value have been recently suggested to be used while comparing the predictive performances of the predictive models' with and without novel biomarkers. Lack of user-friendly statistical software has restricted implementation of novel model assessment methods while examining novel biomarkers. We intended, thus, to develop a user-friendly software that could be used by researchers with few programming skills. We have written a Stata command that is intended to help researchers obtain cut point-free and cut point-based net reclassification improvement index and (NRI) and relative and absolute Integrated discriminatory improvement index (IDI) for logistic-based regression analyses.We applied the commands to a real data on women participating the Tehran lipid and glucose study (TLGS) to examine if information of a family history of premature CVD, waist circumference, and fasting plasma glucose can improve predictive performance of the Framingham's "general CVD risk" algorithm. The command is addpred for logistic regression models. The Stata package provided herein can encourage the use of novel methods in examining predictive capacity of ever-emerging plethora of novel biomarkers.

  6. A Comparative Study to Predict Student’s Performance Using Educational Data Mining Techniques

    Science.gov (United States)

    Uswatun Khasanah, Annisa; Harwati

    2017-06-01

    Student’s performance prediction is essential to be conducted for a university to prevent student fail. Number of student drop out is one of parameter that can be used to measure student performance and one important point that must be evaluated in Indonesia university accreditation. Data Mining has been widely used to predict student’s performance, and data mining that applied in this field usually called as Educational Data Mining. This study conducted Feature Selection to select high influence attributes with student performance in Department of Industrial Engineering Universitas Islam Indonesia. Then, two popular classification algorithm, Bayesian Network and Decision Tree, were implemented and compared to know the best prediction result. The outcome showed that student’s attendance and GPA in the first semester were in the top rank from all Feature Selection methods, and Bayesian Network is outperforming Decision Tree since it has higher accuracy rate.

  7. 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.

  8. 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...

  9. SILTATION IN RESERVOIRS

    African Journals Online (AJOL)

    Calls have been made to the government through various media to assist its populace in combating this nagging problem. It was concluded that sediment maximum accumulation is experienced in reservoir during the periods of maximum flow. Keywords: reservoir model, siltation, sediment, catchment, sediment transport. 1.

  10. Dynamic reservoir well interaction

    NARCIS (Netherlands)

    Sturm, W.L.; Belfroid, S.P.C.; Wolfswinkel, O. van; Peters, M.C.A.M.; Verhelst, F.J.P.C.M.

    2004-01-01

    In order to develop smart well control systems for unstable oil wells, realistic modeling of the dynamics of the well is essential. Most dynamic well models use a semi-steady state inflow model to describe the inflow of oil and gas from the reservoir. On the other hand, reservoir models use steady

  11. 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.

  12. Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

    Directory of Open Access Journals (Sweden)

    Benjamin Stich

    2018-03-01

    Full Text Available Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP, BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY, and tuber yield (TY of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

  13. A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine

    Science.gov (United States)

    Ramakrishnan, Sridhar; Wesensten, Nancy J.; Kamimori, Gary H.; Moon, James E.; Balkin, Thomas J.; Reifman, Jaques

    2016-01-01

    Study Objectives: Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. Methods: We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). Results: The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. Conclusions: The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. Citation: Ramakrishnan S, Wesensten NJ, Kamimori GH, Moon JE, Balkin TJ, Reifman J. A unified model of performance for predicting the effects of sleep and caffeine. SLEEP 2016;39(10):1827–1841. PMID:27397562

  14. Impact of fault damage zones on reservoir performance in the Hibernia oilfield (Jeanne d'Arc Basin, Newfoundland) : an analysis of structural, petrophysical and dynamic well-test data

    Energy Technology Data Exchange (ETDEWEB)

    Porter, J.R.; McAllister, E.; Fisher, Q.J.; Knipe, R.J.; Condliffe, D.M.; Kay, M.A. [Leeds Univ., Leeds (United Kingdom). Dept. of Earth Sciences, Rock Deformation Research Group; Stylianides, G.; Sinclair, I.K. [Hibernia Management and Development Co. Ltd., St. John' s, NL (Canada)

    2005-07-01

    Petroleum reservoirs are typically characterized by combining conventional core analysis results, wire-line log data and sedimentological description with production data. This study emphasized the benefits of including structural analysis of core material as part of general reservoir characterization. In particular, it examined the influence of fault zones on fluid flow within the Hibernia Formation in the Hibernia Oilfield in the Jeanne d'Arc Basin on the Grand Banks of Newfoundland. The geologic setting and background to the Hibernia Field was presented. Fault seal analysis was used in the study to help manage the compartmentalized Hibernia Field. Cross-fault juxtaposition analysis was also integrated with structural logging and petrophysical measurement of core material. The analysis of core material resulted in an increased confidence in production data interpretation. The study also examined how deformation features present within the Hibernia Formation drill cores have the potential to act as baffles or seals to hydrocarbon flow. Deformation features were described with reference to low, intermediate and high clay content fault rocks. It was shown that fault rocks are capable of severely restricting fluid flow, particularly when close to production or