Acceso usuarios
, Yusri Bin Arshad
Purpose: This paper aims to outline a broad-spectrum perspective of the structure of research in artificial intelligence (AI), in the oil and gas industry (OGI) based on bibliometric and distance-based visualisation of similarities (VOS) analysis.
Theoretical framework: The OGI has been one of the major contributors to the world economy. With the increasing energy demand, it has become necessary for the industry to adopt the latest technologies to enhance efficiency, reduce costs, and improve safety. One such technology is AI, which has the potential to revolutionise OGI.
Design/methodology/approach: The paper uses the data from Scopus online database as of April 2023. Based on “key-terms” search results, 251 valid documents were obtained for further analysis using VOS viewer software and Harzing’s Publish or Perish for citation metrics and analysis.
Findings: The finding shows that the Journal of Petroleum Science and Engineering is the field's most relevant journal, with 14 (5.58) published Articles. The People's Republic of China is the most productive country regarding AI research in the OGI. El-Sebakhy's (2009) article is the most cited article, with 113 citations and an average of 8.07 citations per year.
Research, Practical & Social implications: AI could transform OGI. Thus, adopting AI technologies can increase efficiency, reduce costs, and improve safety, also may increase productivity and economic benefits in AI research-intensive countries.
Originality/value: This study provides a comprehensive analysis of the existing AI research in the OGI, utilising bibliometric data and graphical networks.
