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2020 Vol.57, Issue 3 Preview Page

Technical Report

Current Status and Prospects of Artificial Intelligence in the Oil and Gas Exploration and Production Business

석유가스 개발사업의 인공지능기술 활용 현황 및 전망

Baehyun Min1*
,
Seoyoon Kwon1
,
Gayoung Park1
,
Daein Jeong2
,
Haeseon Lee2
민 배현1*
,
권 서윤1
,
박 가영1
,
정 대인2
,
이 혜선2
1Department of Climate and Energy Systems Engineering, Ewha Womans University
2Software Integrated Solutions, Schlumberger
1이화여자대학교 기후·에너지시스템공학과
2Software Integrated Solutions, Schlumberger
* Corresponding Author
30 June 2020. pp. 295-308
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Abstract

This study reviewed the current status and prospects of using artificial intelligence (AI) technology in oil and gas exploration and production (E&P) in facing the era of digital transformation. Beginning with a brief introduction to artificial intelligence, machine learning (ML), and deep learning (DL), this manuscript discusses the following: the use artificial intelligence in E&P projects, an introduction to the state-of-the-art deep learning techniques highlighted in recent E&P projects, an analysis of the trends in global and domestic E&P business, relevant considerations, and concluding remarks. Thus, how the oil and gas E&P business is encouraged to cope with and move forward in the era of digital transformation is examined in detail.

Keywords
Artificial Intelligence
Oil and Gas E&P Business
Digital Transformation
Machine Learning
Deep Learning

이 연구는 디지털 전환의 시대를 맞이하여 석유가스 개발사업의 인공지능기술 활용 현황과 전망을 살펴본다. 인공지능, 머신러닝, 딥러닝에 대한 간략한 소개를 시작으로 석유가스 개발사업에서 인공지능이 어떻게 활용되는지, 다양한 인공지능기술 중 최근 석유가스 개발사업에서 각광받는 딥러닝 기술의 종류에 대한 소개, 국내외 석유가스 개발사업의 딥러닝 기술 활용 현황과 전망, 고찰, 그리고 맺음말로 구성하였다. 이를 토대로 디지털 전환의 시대에서 석유가스 개발사업이 대처하고 나아가야 할 방안에 대하여 논하고자 한다.

키워드
인공지능
석유가스 개발사업
디지털 전환
머신러닝
딥러닝
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Information
  • Publisher :The Korean Society of Mineral and Energy Resources Engineers
  • Publisher(Ko) :한국자원공학회
  • Journal Title :Journal of the Korean Society of Mineral and Energy Resources Engineers
  • Journal Title(Ko) :한국자원공학회지
  • Volume : 57
  • No :3
  • Pages :295-308
  • Received Date : 2020-06-09
  • Revised Date : 2020-06-26
  • Accepted Date : 2020-06-26
  • DOI :https://doi.org/10.32390/ksmer.2020.57.3.295
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