Improving the Accuracy of a Kick-detection System by Reducing Effects of Rig Operational Practices

Deep R. Joshi, S. S. Yalamarty, C. Cheatham, M. Kamyab, Kelly Winklmann, Trish Ross, P. McCormack
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Abstract

Novel methods are presented that update a real-time cloud-based kick-detection system introduced in SPE-208770-MS to handle false kick identifications caused by rig operations. A common weakness in kick-detection systems is false indications of kicks due to rig operations and drilling practices that cause changes in tank volumes. In this work, we will discuss the modifications made to the existing real-time kick-detection system to handle rig operational practices and reduce false positives. The existing kick-detection system analyzes the trends in the drilling data such as tank volumes, flow rates, and pump rates to detect well control events. Extensive field use of this system showed that the rig operations such as transfers between tanks, tank swaps, and adding material to the active tanks have a severe impact on the false-positive rates. Two approaches were developed to handle such operational practices: - Transfer identification: identify transfers between monitored tanks - Comment watcher: Evaluate the rig-memos to check if they might identify an operation that explains the variation in the tank volumes. These approaches were tested with historical wells and live wells. Transfers were identified in several historical wells with help from the operator subject matter experts (SMEs). Thresholds such as the rate of transfer and the window size were tuned to optimally identify transfers. The tuned algorithms correctly identified transfers between monitored tanks with more than 85% accuracy. This workflow was added to the existing kick-detection framework. The efficiency of the kick detection logic depends on dynamically adjusting various thresholds. If any transfers were identified, the thresholds were reset which helped further reduce the false positives by 20% - 25%. For the comment watcher, a keyword library was developed with help from the operator SMEs. This library contained a list of keywords that the rig crew frequently uses in the rig memos to describe the operations. Each keyword from the library was mapped to an alarm type to be suppressed. A workflow was implemented to identify if a rig memo contains a keyword and suppress the respective alarm. The comment watcher feature was then implemented on historical wells along with the transfer identification. These updates resulted in a 40% reduction in false positives while maintaining a 100% true positive identification rate. This work improves the accuracy and efficacy of a previously presented (SPE 208770) real-time cloud- based kick-identification system by detecting and avoiding the impact of rig operations. Features such as transfer identification and comment watcher are added to determine if the changes in the tank volumes can be attributed to rig operations. This update was tested on historical wells and live wells. Working together, these features helped reduce the false positives by up to 40%.
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通过减少钻井作业的影响,提高井涌检测系统的精度
提出了更新SPE-208770-MS中引入的基于云的实时井涌检测系统的新方法,以处理钻机操作引起的假井涌识别。井涌检测系统的一个常见弱点是,由于钻机操作和钻井作业导致的井涌错误指示,会导致储罐体积的变化。在这项工作中,我们将讨论对现有实时井涌检测系统的修改,以处理钻机操作实践并减少误报。现有的井涌检测系统分析钻井数据的趋势,如储罐体积、流量和泵速,以检测井控事件。该系统的大量现场使用表明,储罐之间的转移、储罐交换以及向活性储罐添加材料等钻机操作对误报率有严重影响。为处理此类操作实践,开发了两种方法:—转移识别:识别监控储罐之间的转移—评论观察员:评估钻机备忘录,检查它们是否可以识别出解释储罐容积变化的操作。这些方法在历史井和活井中进行了测试。在运营商主题专家(sme)的帮助下,在几口历史井中确定了转移。对诸如传输速率和窗口大小之类的阈值进行了调优,以最佳地识别传输。调整后的算法正确识别被监测储罐之间的传输,准确率超过85%。该工作流程被添加到现有的井涌检测框架中。kick检测逻辑的效率取决于动态调整各种阈值。如果发现任何转移,则重置阈值,这有助于进一步减少20% - 25%的误报。对于评论观察者,在运营商SMEs的帮助下开发了一个关键字库。该库包含钻井人员在钻井备忘录中经常使用的关键字列表,用于描述作业。日志含义将库中的每个关键字映射为要抑制的告警类型。实现了一个工作流来识别钻井备忘录是否包含关键字,并抑制相应的警报。然后在历史井上实现了评论观察功能,并进行了转移识别。这些更新导致假阳性减少40%,同时保持100%的真阳性识别率。这项工作通过检测和避免钻机操作的影响,提高了先前提出的基于云的实时井涌识别系统(SPE 208770)的准确性和效率。此外,还增加了转移识别和评论观察等功能,以确定储罐体积的变化是否归因于钻机操作。该更新在历史井和生产井上进行了测试。通过协同工作,这些功能帮助将误报率降低了40%。
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