Artificial intelligence techniques and their application in oil and gas industry

被引:0
作者
Sachin Choubey
G. P. Karmakar
机构
[1] Indian Institute of Management,Information Technology and Systems
[2] Indian Institute of Technology,Department of Mining Engineering
来源
Artificial Intelligence Review | 2021年 / 54卷
关键词
Artificial intelligence; Machine learning; Big data analytics; Oil and gas industry;
D O I
暂无
中图分类号
学科分类号
摘要
Data are being continuously generated from various operational steps in the oil and gas industry. The recordings of these data and their proper utilization have become a major concern for the oil and gas industry. Decision making based on predictive as well as inferential data analytics helps in making accurate decisions within a short period of time. In spite of many challenges, the use of data analytics for decision making is increasing on a large-scale in the oil and gas industry. An appreciable amount of development has been done in the above area of research. Many complex problems may now be easily solved using Artificial Intelligence (AI) and Machine Learning (ML) techniques. Historical, as well as real-time data, can be assimilated to achieve higher production by gathering data from the gas/oil wells. Various analytical modeling techniques are now widely being used by the oil and gas sector to make a decision based on data analytics. This paper reviews the recent developments via applications of AI and ML techniques for efficient exploitation of the data obtained, starting from the exploration for crude oil to the distribution of its end products. A brief account of the acceptance and future of these techniques in the oil and gas industry is also discussed. Present work may provide a technical framework for choosing relevant technologies for effectively gaining the information from the large volume of data generated by the oil and gas industry.
引用
收藏
页码:3665 / 3683
页数:18
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