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Real-time Performance Monitoring of Electrical Submersible Pumps in SAGD Process

机译:SAGD过程中电气潜水泵的实时性能监测

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Electrical submersible pump (ESP) is one of the preferred artificial lift systems in upstream oil production because of its wide operating range and endurance to harsh operating environments. In Alberta Canada, about two-thirds of steam assisted gravity drainage (SAGD) wells are equipped with ESPs. Keeping the ESPs long-term operational is one of the primary challenges faced by the operators. ESP failures are a common problem due to various reasons, such as, harsh operating conditions, improper installations, etc. Therefore, the real-time monitoring of ESP performance is indispensable as it can prevent unscheduled well shutdowns and enable preventative maintenance. In this work, aiming at the development of reliable ESP performance monitoring in SAGD process, a monitoring strategy based on a multivariate statistical technique is proposed. The strategy includes a novel first-principles based feature extraction approach, an online model update strategy and a new health index to evaluate ESP health conditions in real time. Test results on real ESP datasets are presented to highlight the efficacy of the proposed algorithm.
机译:电潜水泵(ESP)是上游石油生产中首选人工升力系统之一,因为其宽的操作范围和耐力运行环境。在加拿大艾伯塔省加拿大,大约三分之二的蒸汽辅助重力排水(SAGD)井配有ESP。保持ESPS长期运营是运营商面临的主要挑战之一。 ESP故障是由于各种原因的常见问题,例如,严厉的操作条件,不当安装等等,因此,ESP性能的实时监控是必不可少的,因为它可以防止未安排的良好停机并实现预防性维护。在这项工作中,旨在在SAGD进程中开发可靠的ESP性能监测,提出了一种基于多变量统计技术的监测策略。该策略包括基于新的第一原则的特征提取方法,在线模型更新策略和新的健康指数实时评估ESP健康状况。提出了真实ESP数据集的测试结果以突出所提出的算法的功效。

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