The oil and gas (O&G) industry is a highly dangerous operation in the world, which requires strong Health, Safety and Environment (HSE) management systems to provide timely risk mitigation. The advent of Artificial Intelligence (AI), which includes Internet of Things (IoT), unmanned aerial systems (UAS), digital twin architectures and machine learning and deep learning, has the potential to unlock a new way of approaching HSE management that moves away from reactive to proactive and predictive. This study aims to conduct a systematic literature review (SLR) of the AI-related applications in the field of HSE within O&G operations based on 20 peer-reviewed publications from 2023 to 2025. This review includes predictive maintenance, pipeline leak detection, worker physiological monitoring, drone surveillance and digital twin risk simulation. Thematic synthesis methodology was used to merge and synthesize technology enablers, performance outcomes, implementation barriers and future technology research priorities. The outcomes show that integrating AI can increase pipeline monitoring accuracy to over 90%, cut down on unplanned equipment failures by up to 34% and drastically cut down on the emergency response time. The challenges are related to data governance issues, regulatory weaknesses, cyber security risks and lack of skills in the workforce. The article wraps up with a forward-looking AI-HSE integration framework, in line with international safety standards, and the United Nations Sustainable Development Goals (SDGs), and provides action-oriented guidance to O&G operators, safety practitioners and policy makers.
Ismail Al Zadjali (Fri,) studied this question.
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