Collaborative Optimization Method for Injection and Production Parameters of Water Alternating CO2 Flooding

It has been proved that water alternating CO2 flooding can not only effectively improve oil recovery, but also realize carbon storage, thus achieving a win-win situation for economy and environmental protection. However, it is a very important step to determine the injection-production parameters in the process of water alternating CO2 flooding. The traditional optimization methods of injection-production parameters are generally targeted at the parameters of gas injection Wells, or the control variable method is used to optimize the injection-production parameters successively. However, these methods do not consider the synergistic development effect of injection wells and production wells in the process of gas flooding development. It is not the real optimization of injection-production parameters. Therefore, in this paper, the economic net present value (NPV) of water alternating CO2 flooding is taken as the maximum objective function, and the gas injection time, gas injection speed, total gas injection, gas-water ratio, and gas injection cycle are taken as the optimization variables, and combined with the corresponding constraints, the collaborative optimization mathematical model of gas injection and production parameters of water alternating CO2 flooding is established. The Bayesian adaptive direct search algorithm (BADS) intelligent optimization algorithm was used to solve the problem, then establish the collaborative optimization method of water alternating CO2 flooding injection and production parameters. The application results of HD4 block show that compared with the traditional optimization scheme, the net present value of injection-production collaborative optimization scheme is increased by 190 million yuan, the cumulative oil production is increased by 65,000 square meters, and the water cut is reduced by 1.77%. Therefore, the reliability of the proposed method is verified. The research results show that the intelligent collaborative optimization method for injection and production parameters of water alternating CO2 flooding established in this paper can realize accurate matching of injection and production parameters with remaining oil distribution and reservoir parameters, significantly improving the development effect of water alternating CO2 flooding, effectively improve oil recovery, and provide effective technical support for the adjustment of field development plans.