Drilling Performance and Data Quality Control with Live Digital Twin

R. Karpov, Denis Yurjevich Zubkov, Aleksandr Vitalyevich Murlaev, K. Valiullin
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引用次数: 2

Abstract

The paper presents a solution to the problem of qualitative determination of actual downhole loads and drilling parameters optimization performed employing a dynamic digital well model. The problem of the surface and downhole sensors data quality is disclosed, a solution for an aggregated data QAQC and achieved results are presented. The implementation of the digital platform and the functionality of the dynamic digital twin allowed us to improve the compliance with desired regimes, enabled ensuring the safety of technological operations, allowed us to speed up decision-making while drilling and well completion and commissioning into production. The digital ecosystem allows to timely respond and control operational parameters, to improve and accurately control ROP while minimizing drilling hazards risks and premature drill bit bits wear. The incorporated dynamic digital twin in real-time allows assuring data quality, analyzing activities efficiency, and defining the optimal drilling parameters. The selection of optimal drilling parameters and an increase in ROP are carried out in real-time, based on the analysis of specific mechanical energy. Quality control of sensors plays a key role in the process of evaluating effective weight to bit and associated loads, and in identifying the current friction factor values exhibited downhole. Further on performed trend analysis of the friction factors and respective changes in key drilling parameters allows to track and prevent critical overloads of the drill string, permits to determine the risks of downhole hazards, enables evaluation of well circulation and conditioning activities efficiency in a given interval – allows reducing invisible NPT and the risks of downhole complications. The introduction of a digital ecosystem and a dynamic digital twin allowed us to bring the well construction management process to the next level. Operational response and the decision-making process has been drastically accelerated and improved. Uncertainties associated with an expert's interpretation of drilling states, and subjectivity in the opinions on the effectiveness of processes were eliminated. The negative effect of the human factor and the resulting invisible nonproductive time was minimized. In a short period, the drilling contractor was able to integrate a single digital platform, improve key performance indicators, and involve the field personnel in the full cycle of the technological process of well construction. Field and office personnel, including the driller, can work in a single digital platform, and regardless of the current operation, do always know the true downhole loads, do see the allowable operating envelope and optimal values of the hook load, surface torque, SPP, flow rate, RPM, weight, and torque on the bit, ROP and tripping speeds. The presented method of assessing the quality of the readings of measuring devices and determining the true WOB allows us to optimize the technological parameters during actual drilling. The calculation of the specific mechanical energy is performed based on effective downhole loads transferred to the drill bit. An abnormal increase in the specific mechanical energy notifies the driller to promptly correct the parameters and restore the efficient drilling process. The friction factors are automatically determined during rotation off bottom and tripping operations. Safe corridors and the operational roadmap are re-evaluated every second and are dynamically updated according to the current state of the wellbore and depths.
实时数字孪生钻井性能和数据质量控制
本文提出了一种利用动态数字井模型定性确定实际井下载荷和优化钻井参数的方法。揭示了地面和井下传感器数据质量问题,提出了一种综合数据质量控制的解决方案,并给出了实现结果。数字平台的实施和动态数字孪生的功能使我们能够提高对所需制度的遵从性,确保技术操作的安全性,使我们能够在钻井、完井和投产过程中加快决策速度。数字生态系统允许及时响应和控制操作参数,提高和准确控制ROP,同时最大限度地减少钻井危害风险和钻头过早磨损。集成的动态数字孪生系统可以实时保证数据质量,分析活动效率,并定义最佳钻井参数。在分析比机械能的基础上,实时选择最佳钻井参数,提高机械钻速。传感器的质量控制在评估钻头的有效重量和相关载荷以及确定当前井下显示的摩擦系数值的过程中起着关键作用。此外,对摩擦因素和关键钻井参数的变化进行趋势分析,可以跟踪和防止钻柱的临界过载,确定井下危险的风险,在给定的井段内评估井循环和调节活动的效率,从而减少无形的NPT和井下并发症的风险。数字生态系统和动态数字孪生系统的引入使我们能够将油井施工管理过程提升到一个新的水平。业务反应和决策过程已大大加快和改进。消除了与专家对钻井状态的解释相关的不确定性,以及对工艺有效性意见的主观性。人为因素的负面影响和由此产生的无形的非生产时间被最小化。在短时间内,钻井承包商能够整合一个单一的数字平台,提高关键性能指标,并让现场人员参与到整个建井工艺过程中。现场和办公室人员,包括司钻,都可以在一个数字平台上工作,无论当前的操作如何,都可以始终了解真实的井下载荷,可以看到允许的操作范围和钩载荷、地面扭矩、SPP、流量、RPM、重量、钻头扭矩、ROP和起下钻速度的最佳值。所提出的评估测量设备读数质量和确定真实WOB的方法使我们能够在实际钻井过程中优化技术参数。比机械能的计算是基于传递给钻头的有效井下载荷。当比机械能异常增加时,司钻应及时纠正参数,恢复高效钻井过程。摩擦系数在旋转脱底和起下钻过程中自动确定。每秒钟都会重新评估安全通道和作业路线图,并根据当前井筒状态和深度进行动态更新。
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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