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作 者:李翔宇 闫浩 袁春华 LI Xiangyu;YAN Hao;YUAN Chunhua(Shenyang Ligong University,Shenyang 110159,China)
机构地区:[1]沈阳理工大学自动化与电气工程学院,沈阳110159
出 处:《沈阳理工大学学报》2024年第3期55-62,共8页Journal of Shenyang Ligong University
基 金:国家自然科学基金项目(62173073);辽宁省教育厅高等学校基本科研项目(LJKMZ20220618);辽宁省本科教改优质教学资源建设与共享项目(SBKJGYZ-2021-06)。
摘 要:油井产量计量是油田开采过程中最重要的工作之一,准确计量产量对提高油田开采效率和经济效益至关重要。传统翻斗、两相分离式和示功图等量油技术存在投入大、维护成本高和适应性差等问题。为解决上述问题,提出一种基于改进松鼠搜索算法(improved squirrel search algorithm, ISSA)的油井产量计量方法。通过分析抽油井的工作过程,提出一组描述抽油泵漏失和充满度的故障参数,建立故障条件下的抽油系统过程仿真模型。针对油井故障参数优化问题,提出一种基于食物定位因子的改进松鼠搜索算法,建立基于ISSA的产量计量模型。采用大庆油田数据验证模型,算法平均预测精度为94.52%,表明本方法可为低成本数字油田建设提供支撑。Oil well production measurement is one of the most important tasks in the process of oil field development.Accurately measuring production is crucial for improving the efficiency and eco-nomic benefits of oilfield exploitation.However,in traditional technologies such as bucket eleva-tors,two-phase separation systems,and display graphs there some issues of high investment costs,maintenance expenses,and poor adaptability.To address these problems,a method for oil well pro-duction measurement based on the improved squirrel search algorithm(ISSA)was proposed.By an-alyzing the working process of pumping wells,a set of fault parameters describing pump leakage and filling degree were presented,and a process simulation model of the pumping system under fail-ure conditions was established.Using SSA to optimize the fault parameters of the oil well,a produc-tion measurement model based on electric work graphs was established,and a food position factor was proposed to improve this algorithm.An improved squirrel search algorithm using food location factors was proposed for optimizing fault parameters of oil wells.A production measurement model based on ISSA was also established.Finally,using Daqing oilfield data for verification,the results show that the average prediction accuracy is 94.52%,which provides technical support for low-cost digital oilfield construction.
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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