A response surface model for assessing the impact of well placement and/or well injection/production control optimization approaches on foam injection performance in heterogeneous oil reservoirs

Optimization of well locations and/or well injection/production controls by the trial-and-error method has proven to be computationally expensive and timeconsuming since numerous reservoir simulation studies need to be conducted to arrive at an optimum solution. A computationally inexpensive approach that combines response surface models and optimization algorithms in the optimization process is presented. A two-dimensional heterogeneous reservoir model with an injector and a producer was developed in this study with a reservoir simulator. Seven independent parameters namely bottom-hole pressure of the producer, gas injection rate, surfactant concentration, location of the producer and injector in i and j directions respectively were used. Using the minimum and maximum values of the independent parameters, Box-Behnken Design Method was used to generate fifty-six simulation runs, which were used as input in conducting reservoir simulations to arrive at an output. The input and output datasets were analyzed using experimental design software to generate a response surface model showing the relationship between cumulative oil produced and the seven independent parameters. The model was validated using statistical error analysis, the results of which show the accuracy and reliability of the model in navigating the design space. A comparison was made between cumulative oil produced obtained from the three optimization approaches. Results showed that a coupled well placement and well injection/production control optimization approach resulted in a higher value of cumulative oil produced. This work shows that considering a coupled well placement and well injection/production control optimization approach is preferable during field development planning and can be implemented using proxy models and optimization algorithms.