Enhancing operational efficiency in Nigerian oil exploration: The impact of real-time monitoring technologies on non-productive time

Abstract

Purpose: This study investigates the advancements in real-time monitoring technologies aimed at reducing Non-Productive Time (NPT) in oil exploration in Nigeria, employing systematic content analysis as the research design. Methodology: The study uses systematic content analysis to evaluate recent literature on emerging digital technologies, including Artificial Intelligence (AI) and the Internet of Things (IoT), and their impact on operational efficiency in oil exploration. Results: The findings indicate that AI and IoT in real-time monitoring can enhance predictive maintenance, optimize drilling parameters, and facilitate immediate responses to operational anomalies, reducing NPT by up to 30%. Theoretical Contribution: This study contributes to the discourse on technological innovations in the oil and gas industry, providing actionable insights for stakeholders aiming to enhance operational efficiency in Nigeria's exploration activities. Practical Implications: The study highlights the necessity for investment in digital infrastructure and training, advocating for a strategic approach to modernize Nigeria's oil exploration practices in alignment with global best practices. Sustainable Development Goals (SDGs): SDG 9: Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production; SDG 13: Climate Action; SDG 8: Decent Work and Economic Growth; SDG 7: Affordable and Clean Energy