relation: https://khub.utp.edu.my/scholars/18115/
title: Applications of AI in oil and gas projects towards sustainable development: a systematic literature review
creator: Waqar, A.
creator: Othman, I.
creator: Shafiq, N.
creator: Mansoor, M.S.
description: Oil and gas construction projects are critical for meeting global demand for fossil fuels, but they also present unique risks and challenges that require innovative construction approaches. Artificial Intelligence (AI) has emerged as a promising technology for tackling these challenges, and this study examines its applications for sustainable development in the oil and gas industry. Using a systematic literature review (SLR), this research evaluates research trends from 2011 to 2022. It provides a detailed analysis of how AI suits oil and gas construction. A total of 115 research articles were reviewed to identify original contributions, and the findings indicate a positive trend in AI research related to oil and gas construction projects, especially after 2016. The originality of this study lies in its comprehensive analysis of the latest research on AI applications in the oil and gas industry and its contribution to developing recommendations for improving the sustainability of oil and gas projects. This research�s originality is in providing insight into the most promising AI applications and methodologies that can help drive sustainable development in the oil and gas industry. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.
publisher: Springer Nature
date: 2023
type: Article
type: PeerReviewed
identifier:   Waqar, A. and Othman, I. and Shafiq, N. and Mansoor, M.S.  (2023) Applications of AI in oil and gas projects towards sustainable development: a systematic literature review.  Artificial Intelligence Review, 56 (11).  pp. 12771-12798.  ISSN 02692821     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150642974&doi=10.1007%2fs10462-023-10467-7&partnerID=40&md5=aedb00f69e10f6f9b315026946c45554
relation: 10.1007/s10462-023-10467-7
identifier: 10.1007/s10462-023-10467-7