使用先进机器学习技术的钻井过程数字化-案例研究

Adel Al Shayaa, K. Tamimi, Sara Bakhti, A. Arnaout, G. Thonhauser
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引用次数: 2

摘要

石油和天然气行业正在进入数字化时代,整合数字化转型的新概念对于提高钻井过程的整体效率至关重要。本文将讨论人工智能在该行业的进展,以及如何实施这些解决方案的方法。通过利用自动化实时钻井井下工具、数据分析和预测分析,钻井的数字化转型将提供前所未有的高质量信息流,这是业内从未实现过的。因此,建立了一种基于自动化钻机活动检测的实时测量和处理技术,以提高钻机人员的性能和钻井作业的国际运营公司。对所有钻井作业实施了监控过程,并以作业关键绩效指标(kpi)为基准。
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Drilling Process Digitalization Using Advanced Machine Learning Techniques – Case Study
The digital era is upon us in the oil and gas industry, enforcing the importance of integrating this novel concept of digital transformation is mandatory to improve the overall efficiency of the drilling process. The advances in Artificial Intelligence for the industry, and the methodology of how these solutions can be implemented will be addressed in this paper. The digital transformation of drilling will provide an unprecedented stream of high-quality information that has never been accomplished in the industry, through the utilization of automated real-time drilling downhole tools, data analytics and predictive analysis. Therefore, a real-time measurement and processing technology based on automated rig activities detection was established to improve the performance of the rig crew and drilling operations of an international operating company. A monitoring process was implemented for all drilling operations and benchmarked against operational Key Performance Indicators (KPIs).
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