GA与分层优化结合的掺水集油工艺参数优化OACSTPCD

To minimize the energy consumption of water blending and oil gathering system in oil fields that have entered the ultra-high water cut phase,an optimization of the operational parameters of water blending and oil gathering process was conducted.The optimization model of the operating parameters of the water blending and oil gathering process was developed with water blending temperature,volume,and pressure as the outer-layer decision variables,and the operation schemes of the heat furnaces and water blending pumps as the inner-layer decision variables,aiming for the lowest possible overall energy consumption in water blending and oil gathering process.A solution strategy integrating Genetic Algorithm(GA)and hierarchical optimization was proposed.The water blending temperature was regarded as a gene on the chromosome.Initially,the operation scheme for individual heat furnace and water blending pump was optimized to obtain the minimum oil gathering energy consumption for each corresponding case.Subsequently,through continuous iterative evolution of the population,the optimal operating parameters for the water blending and oil gathering process were obtained.The results indicate that,compared to pre-optimization levels,the water blending temperature is reduced by 8.3℃,the volume of water blending is reduced by 131.6 m3/d,the water blending pressure is reduced by 0.15 MPa,and the overall energy consumption for gathering and transporting each ton of liquid is reduced by 13.64%,demonstrating a favorable optimization outcome.The research results can provide reference for reducing the energy consumption of water blending and oil gathering system in oil fields that have entered the ultra-high water cut phase.