Developing a robust proxy model of CO2 injection: Coupling Box-Behnken design and a connectionist method

The CO2 based enhanced oil recovery methods (EORs) in the petroleum industry are considered as one of the efficient technologies for further production where the natural driving forces become weak. To determine which EOR method is more appropriate for a targeted reservoir, there is a need to develop a reliable and fast tool to predict the performance of the EOR methods due to assumptions and central processing time (CPU) time of reservoir simulations. We develop a promising approach for predicting the ultimate oil recovery factor of the miscible CO2 injection processes. To attain this goal, the least square support vector machine is used to build the proxy model. The Box-Behnken design as a branch of response surface methods is employed to design simulation runs for miscible CO2 injection processes, and the leverage method is applied to validate the proxy model in terms of statistical perspective. An artificial heterogeneous reservoir is used to perform compositional reservoir simulations. Five operational parameters of the miscible CO2 injection process are considered, including bottom-hole flowing pressure (BHP) of injection well (psi), CO2 injection rate (MMSCF/D), injected CO2 concentration (mole fraction), bottom-hole flowing pressure (BHP) of production well (psi), and oil production rate (STB/D). The developed proxy model can be employed to forecast the ultimate oil recovery factor of the miscible CO2 injection operations at the different rock, fluids, and process conditions. The proposed method appears to be an efficient simulation strategy that offers guidelines and screening criteria for the application of the miscible CO2 injection.