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Accident and Incident Analysis in the Oil and Gas Sector Using Artificial Intelligence and Machine Learning

Year: 2024
Type: conference-paper
Abstract: The oil and gas industry is known for its complex operations making it prone to accidents that pose significant risks to human life, economic stability, and the environment. Analyzing and preventing such accidents is critical. This study aims to investigate the human causes of accidents and incidents at oil and gas wells and how artificial intelligence and machine learning (AI/Ml) is used in this sector. The study has used the secondary data from the International Association of Oil and Gas Producers (IOGP) as well as the literature from the Scopus database. It is found that the integration of AI/Ml represents a promising approach to mitigating risks and enhancing safety protocols in the oil and gas industry. Moreover, the common causes of accidents are inadequate supervision (8.9%), inadequate risk assessment (8.7%), and inadequate work procedure (8%), inadequate training (7.8%), defective warning system (5.1%), and lack of awareness (4.2%). Additionally, the AI/Ml are mainly used in the accident prediction of oil and gas pipelines (45%), oil and gas refineries (36%), and oil and gas exploration (21%).
DOI: 10.1016/j.procs.2024.11.113
Language: English
Subfield: Safety Research
Open Access status: diamond
OpenAlex ID: W4405113386
FWCI: 7.42
Cites: 21
Cited by: 8
Related to: 10