Journal of Innovations

Vol. 3, Issue 6

A Conceptual Framework for AI-Driven Predictive Maintenance as a Sustainability Enabler in Oil and Gas Operations

AUTHOR(S)

Sunday Olaniyan and Wakaye Abba Maxwell

ABSTRACT

The oil and gas industry has significant environmental footprints, owing to greenhouse gas contamination, oil leakage, and equipment deterioration from system breakdowns coupled with conventional maintenance methods. The combination of Artificial Intelligence (AI)-driven predictive maintenance with machine learning, IoT sensors, and data analytics functions as a principal solution to monitor infrastructure against potential failures. This paper explores AI predictive maintenance systems for environmental benefits which consist of minimized emissions, disaster prevention, and hurdles with ethical implications. Going forward three innovation opportunities can be explored, such as advanced AI models for more precise failure, blockchain integration, and renewable energy combination systems. This technological advancement of the oil and gas sector both decreases environmental harm and helps the world achieve sustainability goals. By implementing AI-driven solutions, the industry can enhance efficiency while reducing its environmental impact, thereby ultimately contributing to a cleaner yet energy-resilient future.

DOI

https://doi.org/10.62470/1f257133

CITE THIS ARTICLE 

Olaniyan, S. and Maxwell, W. A. (2025). A Conceptual Framework for AI-Driven Predictive Maintenance as a Sustainability Enabler in Oil and Gas Operations, Journal of Innovations, 3(6), 1-26. https://doi.org/10.62470/1f257133