Optimization of intermittent oil recovery mechanism based on multi-objective genetic algorithm

With the continuous exploitation of oil fields, the problem of long-term inefficient operation of some pumping units is common in major oil fields in China. The intermittent oil recovery mechanism can effectively avoid the wear and tear of empty pumping while reducing electrical energy consumption. The Pareto multi-objective genetic algorithm is used to optimize the optimal downtime of the pumping units from the perspective of energy saving in the oil recovery system, to maximize the efficiency of oil recovery while minimizing power consumption. A comparison of the experimental results showed that the intermittent oil recovery mechanism was optimized to save 21.45% of energy consumption and improve the system efficiency by 38.85%. This method solves the problems of empty pumping and inefficiency of pumping units and achieves the purpose of reducing the mechanical wear and tear of oil recovery machines, saving electrical energy, and improving the overall development benefit of the oil field.