Deploying Dynamic Trend-Based Monitoring System to Deliver Real Time Drilling Decision

Bobbywadi Richard, M. S. Saarani, S. Sulaiman, M. M. H. Meor Hashim, M. Arriffin, Rohaizat Ghazali
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Abstract

Significant technical challenges are prominent in today's oil and gas drilling operations, especially in remote locations with increasingly difficult geological settings. Stuck pipe incidents have become a major operational challenge, with events typically resulting in substantial amounts of lost time and associated costs. Real-time monitoring has emerged as an important tool to achieve drilling optimization in avoiding downtime, particularly stuck pipe events. With the addition of a predictive monitoring system, this process becomes much more effective and competent. Predictive monitoring is used for advanced real-time monitoring in the remote centre and operational workflows to aid in the drilling execution of complex or critical well sections. The emphasis will be on reducing the complexity of real-time data analysis by exploiting trends and anomalies between modelled and actual data to monitor wellbore conditions. This monitoring system and trend-based predictive capability enable drilling teams to detect borehole changes and take preventive action up to several hours in advance. Predictive monitoring can provide early warning of stuck pipe symptoms, allowing the rig and operations team to take corrective and step-by-step actions. The circumstances that lead to the stuck pipe can be difficult to detect as various factors may indicate potential problems. These are frequently missed until the situation has progressed to the point where the drill string becomes stuck. This system could have provided the rig crew with advance notice of changes in downhole conditions. An example of predictive monitoring adoption in a highly deviated extended reach well (ERD), with a 12,000ft long horizontal section is presented. It is exceptionally challenging in terms of geomechanics perspective as well as the well design. Predictive monitoring was implemented to assist drilling operation for the sidetracked well, and it had been completed successfully with minor hole condition issues. The predictive monitoring system is built around a trio of tightly coupled real-time dynamic models consisting of hydraulic, mechanical, and thermodynamic that simulate the wellbore state and physical processes during drilling operations. These models work simultaneously in a seamless process to assess drilling performance, borehole conditions, and related associated risks. It uses dynamic modelling to accurately model key drilling parameters and variables, allowing better monitoring.
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采用动态趋势监测系统,提供实时钻井决策
在当今的石油和天然气钻井作业中,特别是在地质条件越来越困难的偏远地区,重大的技术挑战尤为突出。卡钻事故已成为主要的作业挑战,通常会造成大量的时间损失和相关成本。实时监测已经成为实现钻井优化的重要工具,以避免停工,特别是卡钻事件。随着预见性监测系统的加入,这一过程变得更加有效和胜任。预测监测用于远程中心和作业流程的高级实时监测,以帮助复杂或关键井段的钻井执行。重点是通过利用模型数据和实际数据之间的趋势和异常来监测井筒状况,从而降低实时数据分析的复杂性。该监测系统和基于趋势的预测能力使钻井队能够提前数小时检测井眼变化并采取预防措施。预测监测可以为卡钻现象提供早期预警,使钻机和作业团队能够采取纠正措施,逐步采取行动。导致卡钻的情况很难发现,因为各种因素都可能表明潜在的问题。在钻柱卡钻之前,这些工具经常会被遗漏。该系统可以提前通知钻井队井下情况的变化。介绍了一个在大斜度大位移井(ERD)中采用预测监测的实例,该井的水平段长度为12,000英尺。从地质力学角度和井设计角度来看,这是非常有挑战性的。为了辅助侧钻井的钻井作业,该公司实施了预测监测,并成功完成了该侧钻井的钻井作业,只出现了较小的井况问题。预测监测系统建立在三个紧密耦合的实时动态模型上,包括水力、机械和热力学模型,模拟钻井作业期间的井筒状态和物理过程。这些模型在无缝过程中同时工作,以评估钻井性能、井眼条件和相关风险。它使用动态建模来准确地模拟关键钻井参数和变量,从而更好地进行监测。
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