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Title

AUTOMATED RESERVOIR HISTORY MATCHING USING GENETIC ALGORITHM IN ONE OF IRANIAN OIL RESERVOIR

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Abstract

 HISTORY MATCHING IS THE PROCESS OF UPDATING RESERVOIR MODEL USING PRODUCTION DATA. IT IS NECESSARY BEFORE FORECASTING FUTURE PRODUCTION. THE PROCESS IS NORMALLY CARRIED OUT BY RESERVOIR SIMULATORS, WHICH IS VERY TIME-CONSUMING. AS A RESULT, ONLY A SMALL NUMBER OF SIMULATION RUNS ARE CONDUCTED AND THE HISTORY MATCHING RESULTS ARE NORMALLY UNSATISFACTORY. A GENETIC ALGORITHM IS APPLIED TO THE PROBLEM OF CONDITIONING THE ROCK PROPERTIES OF A RESERVOIR MODEL ON HISTORIC PRODUCTION DATA. THIS IS A DIFFICULT OPTIMIZATION PROBLEM WHERE EACH EVALUATION OF THE OBJECTIVE FUNCTION IMPLIES A FLOW SIMULATION OF THE WHOLE RESERVOIR. DUE TO THE HIGH COMPUTING COST OF THIS FUNCTION, IT IS IMPERATIVE TO MAKE USE OF AN EFFICIENT OPTIMIZATION METHOD TO FIND A NEAR OPTIMAL SOLUTION USING AS FEW ITERATIONS AS POSSIBLE. IN THIS STUDY WE HAVE APPLIED A GENETIC ALGORITHM TO SOLVE THIS PROBLEM. IN ORDER TO RUN RESERVOIR SIMULATIONS COMPOSITIONAL SIMULATOR E300Ò APPLIED TO BE COMPARED WITH OBSERVED DATA. THE MEAN SQUARE ERROR IS USED AS OUR FITNESS FUNCTION THAT SHOULD BE MINIMIZED. USING MATLAB GENETIC ALGORITHM TOOLBOX WITH 3 VARIABLES WILL RESULT IN MATCHING BOTTOM HOLE PRESSURE HISTORY OF WELL NO.2 OF THE RESERVOIR.

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    APA: Copy

    Nouri, S.M.A., & Soltani Soulgani, B.. (2014). AUTOMATED RESERVOIR HISTORY MATCHING USING GENETIC ALGORITHM IN ONE OF IRANIAN OIL RESERVOIR. INTERNATIONAL CHEMICAL ENGINEERING CONGRESS AND EXHIBITION. SID. https://sid.ir/paper/916628/en

    Vancouver: Copy

    Nouri S.M.A., Soltani Soulgani B.. AUTOMATED RESERVOIR HISTORY MATCHING USING GENETIC ALGORITHM IN ONE OF IRANIAN OIL RESERVOIR. 2014. Available from: https://sid.ir/paper/916628/en

    IEEE: Copy

    S.M.A. Nouri, and B. Soltani Soulgani, “AUTOMATED RESERVOIR HISTORY MATCHING USING GENETIC ALGORITHM IN ONE OF IRANIAN OIL RESERVOIR,” presented at the INTERNATIONAL CHEMICAL ENGINEERING CONGRESS AND EXHIBITION. 2014, [Online]. Available: https://sid.ir/paper/916628/en

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