人工智能技术在石油作业中的应用综述

Q1 Earth and Planetary Sciences Petroleum Research Pub Date : 2023-06-01 DOI:10.1016/j.ptlrs.2022.07.002
Saeed Bahaloo , Masoud Mehrizadeh , Adel Najafi-Marghmaleki
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引用次数: 6

摘要

在过去几年中,人工智能(AI)和机器学习(ML)技术的使用作为石油行业的趋势技术受到了相当大的关注。新工具和现代技术的使用创造了大量结构化和非结构化数据。作为一个重要的调查领域,以更快的速度组织和处理这些信息,用于油田开发和管理的绩效评估和预测。利用传统方法预测作业特征所面临的各种困难已引导学术界和工业界进行研究,重点关注ML和数据驱动方法在勘探和生产作业中的应用,以实现更准确的预测,从而改进决策过程。本研究综述了AI和ML技术在石油工业中的用例和应用,以优化上游流程,如油藏研究、钻井和生产工程。评估了与手术参数预测的常规方法相关的挑战,并介绍了通过采用数据驱动方法优化性能以增强决策工作流程的用例。此外,还讨论了人工智能发展和影响石油和天然气行业的可能情景,以及它在未来可能如何改变石油和天然天然气行业。
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Review of application of artificial intelligence techniques in petroleum operations

In the last few years, the use of artificial intelligence (AI) and machine learning (ML) techniques have received considerable notice as trending technologies in the petroleum industry. The utilization of new tools and modern technologies creates huge volumes of structured and un-structured data. Organizing and processing of these information at faster pace for the performance assessment and forecasting for field development and management is continuously growing as an important field of investigation. Various difficulties which were faced in predicting the operative features by utilizing the conventional methods have directed the academia and industry toward investigations focusing on the applications of ML and data driven approaches in exploration and production operations to achieve more accurate predictions which improves decision-making processes. This research provides a review to examine the use cases and application of AI and ML techniques in petroleum industry for optimization of the upstream processes such as reservoir studies, drilling and production engineering. The challenges related to routine approaches for prognosis of operative parameters have been evaluated and the use cases of performance optimizations through employing data-driven approaches resulted in enhancement of decision-making workflows have been presented. Moreover, possible scenarios of the way that artificial intelligence will develop and influence the oil and gas industry and how it may change it in the future was discussed.

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来源期刊
Petroleum Research
Petroleum Research Earth and Planetary Sciences-Geology
CiteScore
7.10
自引率
0.00%
发文量
90
审稿时长
35 weeks
期刊最新文献
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