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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....

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Main Authors:	Wu, Jingsong, Jiang, Mingzheng, Dong, Kangxing, Yang, Hukun
Format:	Conference Proceeding
Language:	English
Subjects:	Economics Energy conservation Energy consumption energy saving intermittent pumping multi-objective genetic algorithm oil extraction efficiency Oils Optimization methods Power demand pumping units Pumps
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creator	Wu, Jingsong Jiang, Mingzheng Dong, Kangxing Yang, Hukun
description	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.
doi_str_mv	10.1109/CCDC58219.2023.10327418
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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%. 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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.</abstract><pub>IEEE</pub><doi>10.1109/CCDC58219.2023.10327418</doi><tpages>5</tpages></addata></record>
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ispartof	2023 35th Chinese Control and Decision Conference (CCDC), 2023, p.2566-2570
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language	eng
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source	IEEE Xplore All Conference Series
subjects	Economics Energy conservation Energy consumption energy saving intermittent pumping multi-objective genetic algorithm oil extraction efficiency Oils Optimization methods Power demand pumping units Pumps
title	Optimization of intermittent oil recovery mechanism based on multi-objective genetic algorithm
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