AI in Oil and Gas: Predicting Equipment Failures and Maximizing Uptime

Author(s)	Ramesh Betha
Country	United States
Abstract	The oil and gas industry faces unprecedented challenges in maintaining operational efficiency while managing aging infrastructure and increasing regulatory pressures. This paper explores the transformative potential of artificial intelligence (AI) in predicting equipment failures and maximizing uptime across upstream, midstream, and downstream operations. Through analysis of real-world implementations and emerging technological frameworks, we demonstrate how machine learning algorithms, particularly deep learning and time-series analysis, can revolutionize traditional maintenance practices. The research presents a comprehensive examination of current AI applications in equipment monitoring, predictive maintenance, and operational optimization, while addressing key challenges in data quality, integration, and workforce adaptation
Keywords	Artificial Intelligence, Machine Learning, Oil and Gas Industry, Predictive Maintenance, Equipment Reliability, Industrial IoT
Field	Engineering
Published In	Volume 12, Issue 1, January-March 2021
Published On	2021-02-09
Cite This	AI in Oil and Gas: Predicting Equipment Failures and Maximizing Uptime - Ramesh Betha - IJSAT Volume 12, Issue 1, January-March 2021. DOI 10.5281/zenodo.14866257
DOI	https://doi.org/10.5281/zenodo.14866257
Short DOI	https://doi.org/g84xmh

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