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      Applications of AI in oil and gas projects towards sustainable development: a systematic literature review

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          Abstract

          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.

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          Most cited references105

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          Is Open Access

          Literature review as a research methodology: An overview and guidelines

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            Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review

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              Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities

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                Author and article information

                Contributors
                ahsan_21002791@utp.edu.my
                idris_othman@utp.edu.my
                nasirshafiq@utp.edu.my
                muhammadshoaibmansoor594@gmail.com
                Journal
                Artif Intell Rev
                Artif Intell Rev
                Artificial Intelligence Review
                Springer Netherlands (Dordrecht )
                0269-2821
                1573-7462
                23 March 2023
                : 1-28
                Affiliations
                [1 ]GRID grid.444487.f, ISNI 0000 0004 0634 0540, Department of Civil and Environmental Engineering, , Universiti Teknologi PETRONAS, ; Bandar Seri Iskandar, 32610 Tronoh, Perak Malaysia
                [2 ]GRID grid.412782.a, ISNI 0000 0004 0609 4693, Department of Civil Engineering, , University of Sargodha, ; Sargodha, 40100 Punjab Pakistan
                Article
                10467
                10.1007/s10462-023-10467-7
                10034239
                eadc0ce4-bf77-4974-a268-7bffab98a6a6
                © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

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                artificial intelligence (ai),oil and gas projects,sustainable development,systematic literature review

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