Application of Optimized Proxy Algorithm for History Matching Using Response Surface and Genetic Algorithm, a Case Study: in One of the Big Oil Reservoirs

One of the most important sections in fulfilled study (FFS) and master development plan is history matching which plays an important role in production scenarios and future production plan of reservoir. It would be a challenge for reservoir engineering due to lots of parameters and uncertainties during reservoir study which need lots of simulation runs to reach good match for responses in conventional mechanism of history matching. However, for accelerating history matching part, new methods which called as assisted or automated history matching (AHM) have been established. In this paper, an approach for automated history matching (AHM) was applied in a real brown field with 14 wells with multiple responses located in south of Iran. The main important features of the proposed algorithm were defining a proxy model which was a response surface method in which 21 model parameters were incorporated based on cubic centered face method. Response surface method (RSM) has been employed to create the proxy model. The optimization algorithms utilized in this research were genetic algorithm (GA) and particle swarm optimization (PSO). Proxy model was successfully constructed using 256 samples leading into R2 of 0.9 on dataset with good results on GA.