Optimization of Intermittent Oil Recovery System Based on Improved NSGA-Ⅱ Algorithm
For low-permeability oil wells,the adoption of intermittent oil recovery mechanism can effectively avoid wear and tear of empty pumping and reduce power consumption simultaneously.Through analyzing the varia-tion of submergence depth and formation flowing pressure with the production time of pumping wells,from the per-spective of energy saving of the system,a multi-objective optimization model for intermittent oil recovery system was established,in order to maximize the total oil production and minimize the energy consumption.Then,the NSGA-Ⅱ was introduced and improved to solve the multi-objective optimization model of intermittent oil recovery system.Finally,the diversity and convergence of Pareto optimal solution obtained from the improved NSGA-Ⅱ algorithm were used to reasonably optimize the optimal stop time of the pumping unit,maximizing oil recovery efficiency while minimizing power consumption.The comparison of test results shows that the optimization of intermittent oil recover-y mechanism based on Pareto multi-objective genetic algorithm is obviously advantageous in effectively reducing power consumption while optimizing the system efficiency.The research results provide strong method and technical support for the improvement and optimization of intermittent oil recovery mechanism of oil wells.
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