: 10.62796/pijst
Big Data and AI in Combating Oil Theft and Resource Management
N. E. Bello, Kano State Polytechnic, Kano, Nigeria.
G. Nwosu, Federal Polytechnic, Ado-Ekiti, Nigeria.
Published Date: 05-12-2024 Issue: Vol. 1 No. 12 (2024): December 2024 Published Paper PDF: Download
Abstract- This study investigates the transformative role of Big Data and Artificial Intelligence (AI) in combating oil theft and enhancing petroleum resource management, with a specific focus on Nigeria. Oil theft poses significant economic, security, and environmental challenges, undermining government revenues, corporate profitability, and national stability. By leveraging Big Data analytics from sensor networks, transactional records, and satellite imagery, theft patterns can be detected early, enabling proactive interventions. AI techniques—such as machine learning, neural networks, support vector machines, and anomaly detection—facilitate predictive maintenance, resource optimization, and automated decision-making in oilfield operations. The integration of these technologies creates a synergistic effect, allowing for real-time monitoring, anomaly identification, and predictive analytics across the petroleum supply chain. Emerging innovations including the Internet of Things (IoT), blockchain platforms, and remote monitoring systems further enhance transparency, traceability, and security. However, challenges persist regarding data integration, scalability, and ethical considerations such as privacy and fairness. The study emphasizes the need for supportive policies, regulatory cooperation, and international collaboration. Overall, Big Data and AI present robust, data-driven solutions for mitigating oil theft, optimizing resource allocation, and promoting sustainability in the petroleum industry. Keywords: Big Data, Artificial Intelligence, Oil Theft, Resource Management, Nigeria, Predictive Analytics, Blockchain.
Published Date: 05-12-2024 Issue: Vol. 1 No. 12 (2024): December 2024 Published Paper PDF: Download
Abstract- This study investigates the transformative role of Big Data and Artificial Intelligence (AI) in combating oil theft and enhancing petroleum resource management, with a specific focus on Nigeria. Oil theft poses significant economic, security, and environmental challenges, undermining government revenues, corporate profitability, and national stability. By leveraging Big Data analytics from sensor networks, transactional records, and satellite imagery, theft patterns can be detected early, enabling proactive interventions. AI techniques—such as machine learning, neural networks, support vector machines, and anomaly detection—facilitate predictive maintenance, resource optimization, and automated decision-making in oilfield operations. The integration of these technologies creates a synergistic effect, allowing for real-time monitoring, anomaly identification, and predictive analytics across the petroleum supply chain. Emerging innovations including the Internet of Things (IoT), blockchain platforms, and remote monitoring systems further enhance transparency, traceability, and security. However, challenges persist regarding data integration, scalability, and ethical considerations such as privacy and fairness. The study emphasizes the need for supportive policies, regulatory cooperation, and international collaboration. Overall, Big Data and AI present robust, data-driven solutions for mitigating oil theft, optimizing resource allocation, and promoting sustainability in the petroleum industry. Keywords: Big Data, Artificial Intelligence, Oil Theft, Resource Management, Nigeria, Predictive Analytics, Blockchain.
