Machine learning for drilling applications: A review

IF 4.9 2区 工程技术 Q2 ENERGY & FUELS
Ruizhi Zhong , Cyrus Salehi , Ray Johnson Jr
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引用次数: 13

Abstract

In the past several decades, machine learning has gained increasing interest in the oil and gas industry. This paper presents a comprehensive review of machine learning studies for drilling applications in the following categories: (1) drilling fluids; (2) drilling hydraulics; (3) drilling dynamics; (4) drilling problems; and (5) miscellaneous drilling applications. In each study, the machine learning algorithm(s), sample size, inputs and output(s), and performance are extracted. In addition, similarities of studies in each category are summarized and recommendations are made for future development.

钻井应用中的机器学习:综述
在过去的几十年里,机器学习在石油和天然气行业引起了越来越多的兴趣。本文对机器学习在钻井应用中的研究进行了全面综述,主要包括以下几个方面:(1)钻井液;(2)钻井液压;(3)钻井动力学;(4)钻孔问题;(5)各种钻井应用。在每项研究中,都提取了机器学习算法、样本量、输入和输出以及性能。此外,总结了各类别研究的相似之处,并对今后的发展提出了建议。
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来源期刊
Journal of Natural Gas Science and Engineering
Journal of Natural Gas Science and Engineering ENERGY & FUELS-ENGINEERING, CHEMICAL
CiteScore
8.90
自引率
0.00%
发文量
388
审稿时长
3.6 months
期刊介绍: The objective of the Journal of Natural Gas Science & Engineering is to bridge the gap between the engineering and the science of natural gas by publishing explicitly written articles intelligible to scientists and engineers working in any field of natural gas science and engineering from the reservoir to the market. An attempt is made in all issues to balance the subject matter and to appeal to a broad readership. The Journal of Natural Gas Science & Engineering covers the fields of natural gas exploration, production, processing and transmission in its broadest possible sense. Topics include: origin and accumulation of natural gas; natural gas geochemistry; gas-reservoir engineering; well logging, testing and evaluation; mathematical modelling; enhanced gas recovery; thermodynamics and phase behaviour, gas-reservoir modelling and simulation; natural gas production engineering; primary and enhanced production from unconventional gas resources, subsurface issues related to coalbed methane, tight gas, shale gas, and hydrate production, formation evaluation; exploration methods, multiphase flow and flow assurance issues, novel processing (e.g., subsea) techniques, raw gas transmission methods, gas processing/LNG technologies, sales gas transmission and storage. The Journal of Natural Gas Science & Engineering will also focus on economical, environmental, management and safety issues related to natural gas production, processing and transportation.
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