2012
DOI: 10.1007/s13202-012-0023-0
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Experimental Design in reservoir simulation: an integrated solution for uncertainty analysis, a case study

Abstract: Quantification of uncertain parameters in oil reservoirs is one of the major issues of concern. In underdeveloped reservoirs, there are many uncertain parameters affecting production forecast which plays a main role in reservoir management and decision making in development plan. To study the effect of uncertain parameters on the behavior of a reservoir and to forecast the probabilistic production of the reservoir, the simulator has to be run too many times with different entries for uncertain parameters. To a… Show more

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Cited by 9 publications
(6 citation statements)
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“…The authors [31] made the comparison of SRM with least square support vector machine. Use of experimental design to develop response surface [32][33][34][35][36][37][38][39][40][41], integrated with Monte Carlo simulations to characterise the response surface and to estimate the uncertainty [42,43]. Application of Bayesian multi-stage MCMC approach, based on an approximation with a linear expansion to reduce high computational costs [44], more accurately obtained model uncertainty and also assists in productionforecast business decisions [45], with Bayesian workflow based on two-step MCMC inversion [46].…”
Section: Background Studies Of Proxy Modelmentioning
confidence: 99%
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“…The authors [31] made the comparison of SRM with least square support vector machine. Use of experimental design to develop response surface [32][33][34][35][36][37][38][39][40][41], integrated with Monte Carlo simulations to characterise the response surface and to estimate the uncertainty [42,43]. Application of Bayesian multi-stage MCMC approach, based on an approximation with a linear expansion to reduce high computational costs [44], more accurately obtained model uncertainty and also assists in productionforecast business decisions [45], with Bayesian workflow based on two-step MCMC inversion [46].…”
Section: Background Studies Of Proxy Modelmentioning
confidence: 99%
“…The authors [5] mentioned that, in an experiment, one or more variables could be changed to quantify the effect of inputs on outputs (response variables). ED is used to avoid the time-consuming process to captured all changes with the minimum number of simulator runs [31,38]. The authors [34,38,41) show many studies in petroleum engineering which applied the ED methodology.…”
Section: Experimental Designmentioning
confidence: 99%
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“…One variable at a time method is a static sensitivity common in classical laboratory experiments. However, its application for screening large number of uncertainties has been reported [8].…”
Section: Introductionmentioning
confidence: 99%
“…Data-fits are the most common type of proxy model in uncertainty quantification and probabilistic forecasting in petroleum fields Moeinikia and Alizadeh, 2012;. However, modeling a reliable data-fit proxy model is difficult due to the high non-linearity between input (reservoir properties) and output (production, injection, and economic forecasts) variables.…”
Section: Introductionmentioning
confidence: 99%