Mud Motor Digital Maintenance with an Industry-Unique PHM Solution

D. Belov, S. Rocchio, Zhengxin Zhang, Wei Chen, Samba Ba, Eimund Liland, A. Kolyshkin, Yueling Shen, Josh Scribbins, Henry Massie, Kent Phillips
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Abstract

The ability to analyze drilling data to obtain continuous monitoring statistics of the drilling process and make prompt decisions are two important elements of a successful drilling operation. A mud motor is one of the important components of the downhole assembly, which enables the drill bit to penetrate the rock during drilling a well. Correctly predicting mud motor failure and the remaining useful life of the components are essential for obtaining drilling efficiency, avoiding costly operational expenses, and achieving timely maintenance. The remaining useful life indicator with low uncertainty identifies the life cycle of mud motors by preventing redundant maintenance and costly drilling operation failures. This paper presents an industry-unique prognostics and health-management (PHM) solution for monitoring and maintaining the mud motor condition. This solution combines three algorithms, including a power section PHM algorithm, lower-end critical connections PHM algorithm, and mud motor degradation algorithm. The workflow solution allows for obtaining valuable information about the mud motor condition at the system and component levels. The power section PHM algorithm, based on a remaining useful life prediction for the mud motor's power section, provides information about the elastomer condition inside of the stator as a percentage of the remaining life cycle. The lower-end critical connections PHM algorithm estimates the remaining useful life of the mud motor's lower-end connections. Both algorithms are component level; i. e., they help to improve managing the life cycle of the appropriate components. The mud motor degradation algorithm is a system-level algorithm. This algorithm uses drilling data to compute the severity of mud motor degradation; thus, identifying possible problems with the mud motor as a complete system. The PHM solution helps to prevent expensive mud motor failure. Furthermore, the solution provides the opportunity to perform additional drilling runs before the motor components must be retired or removed for maintenance. The significant advantage of applying the PHM solution is it only makes use of existing drilling measurements and does not require any special downhole equipment. The mud motor PHM solution is currently in use by one of the biggest oil & gas service company worldwide. In addition to presenting the three algorithms, this paper presents field application case studies that demonstrate the commercial value and efficiency gains achieved by their use. Significant sustainability benefits have been achieved by using the power section and mud motor degradation algorithms due to their assistance in drilling applications.
泥浆马达数字化维护与行业独特的PHM解决方案
分析钻井数据以获得钻井过程的连续监测统计数据并及时做出决策的能力是成功钻井作业的两个重要因素。泥浆马达是井下钻具组合的重要部件之一,它使钻头能够在钻井过程中穿透岩石。正确预测泥浆马达故障和组件的剩余使用寿命对于提高钻井效率、避免昂贵的操作费用和实现及时维护至关重要。剩余使用寿命指标具有低不确定性,可通过防止冗余维护和昂贵的钻井作业故障来确定泥浆马达的生命周期。本文提出了一种行业独特的预测和健康管理(PHM)解决方案,用于监测和维护泥浆运动状态。该解决方案结合了三种算法,包括功率段PHM算法、低端关键连接PHM算法和泥浆马达退化算法。该工作流程解决方案允许在系统和组件级别获取有关泥浆马达状况的有价值信息。动力段PHM算法基于泥浆马达动力段的剩余使用寿命预测,提供定子内部弹性体状况占剩余使用周期百分比的信息。低端关键连接PHM算法可估算泥浆马达低端连接的剩余使用寿命。两种算法都是组件级的;也就是说,它们有助于改进对适当组件的生命周期的管理。泥浆马达退化算法是一种系统级算法。该算法利用钻井数据计算泥浆马达退化的严重程度;因此,识别泥浆马达作为一个完整系统可能存在的问题。PHM解决方案有助于防止昂贵的泥浆马达故障。此外,该解决方案还提供了在电机组件必须退役或拆卸维修之前进行额外钻井作业的机会。应用PHM解决方案的显著优势是,它只利用现有的钻井测量,不需要任何特殊的井下设备。泥浆马达PHM解决方案目前被全球最大的油气服务公司之一所使用。除了介绍这三种算法外,本文还介绍了现场应用案例研究,证明了它们的商业价值和效率的提高。通过使用动力部分和泥浆马达降解算法,由于它们在钻井应用中的辅助作用,已经取得了显著的可持续性效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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