Abstract
Crude Oil bunkering and illegal siphoning remain a threat in the oil and gas industry, with its associated mind-boggling economic loss, environmental degradation, and hours of production losses. Traditional surveillance and monitoring systems have failed to provide real-time detection and intervention as they are manual surveillance-based. This review reports the application of Artificial Intelligence (AI) in oil theft prevention and detection via machine learning, computer vision, and predictive analytics. Case studies centered on high-risk oil producing areas where these activities are often carried out. These include the Gulf of Mexico in North America, Niger Delta regions of Nigeria and Anambra State Nigeria, confirm the effect of AI-based surveillance in preventing these crimes. In Anambra State, studies recorded a 25% reduction in theft, 30% in vandalism, and 20% in sabotage after the installation of AI-based security facilities. These confirm the positive effect of AI theft detection capacity. Similarly, AI-based predictive analytics in the Niger Delta improved real-time detection of anomalies, where the response time improved and meaningful reductions were recorded in the illegal siphoning of oil. In the Gulf of Mexico, AI-based monitoring of pipelines were effective in detecting and preventing unauthorized entry, with the enhancement of asset security. The findings of this review include the confirmation of the revolutionary effect of AI in the safeguarding of oil and gas infrastructures, recommending investment in intelligent surveillance devices and the implementation of strong regulatory frameworks in fighting the threat of illicit activities in the oil and gas industry.
Keywords
Artificial Intelligence (AI); Oil Bunkering; Illegal Theft Detection; Machine Learning; Pipeline Surveillance.
Citations
IRE Journals:
Afolabi Ridwan Bello
"AI-Assisted Crude Oil Bunkering and Illegal Theft Detection in the Oil and Gas Industry" Iconic Research And Engineering Journals Volume 8 Issue 10 2025 Page 369-379
IEEE:
Afolabi Ridwan Bello
"AI-Assisted Crude Oil Bunkering and Illegal Theft Detection in the Oil and Gas Industry" Iconic Research And Engineering Journals, 8(10)
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