Study on optimization of well washing parameters and efficiency improvement of oil field water injection wells based on intelligent optimization algorithm

In this paper, the optimization of well washing parameters and efficiency improvement of oil field water injection wells based on intelligent optimization algorithm are studied. Well washing of water injection wells is a key process in oil exploitation. The traditional well washing parameter setting mostly depends on experience or trial and error method, which has problems of low efficiency and high cost. In this paper, a hybrid optimization framework combining genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to optimize the modeling of key parameters such as well flushing displacement, time, pressure and properties of well flushing fluid. The experimental verification of 6 water injection wells in an oilfield in Bohai Sea shows that the optimized well flushing parameters significantly reduce the displacement, time and pressure, the average cleaning rate increases from 82.3% to 94.7%, and the total cost decreases by 32.6%. The research shows that the intelligent optimization algorithm can effectively improve the well washing efficiency, reduce energy consumption and cost, and provide scientific basis and technical support for the intelligent well washing operation of oil field water injection wells.