Predictive maintenance in oil and gas facilities, leveraging ai for asset integrity management

Chuka Anthony Arinze 1, Izionworu, Vincent Onuegbu 2, 3, *, Daniel Isong 4, Cosmas Dominic Daudu 5 and Adedayo Adefemi 6

1 Independent Researcher, Port Harcourt, Rivers State. Nigeria.
2 Chemical/Petrochemical Engineering, Faculty of Engineering, Rivers State University, Nigeria.
3 Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
4 Independent Researcher, Port Harcourt, Nigeria.
5 Nigeria LNG Limited, Bonny Island.
6 Chevron Nigeria Limited.
 
Review
International Journal of Frontiers in Engineering and Technology Research, 2024, 06(01), 016–026​.
Article DOI: 10.53294/ijfetr.2024.6.1.0026
Publication history: 
Received on 06 February 2024; revised on 12 March 2024; accepted on 15 March 2024
 
Abstract: 
This paper explores the application of AI in predictive maintenance within oil and gas facilities, discussing its benefits, challenges, and future prospects. Through the integration of AI-driven analytics and real-time data monitoring, oil and gas companies can enhance their asset integrity management practices, ultimately driving cost savings and operational excellence. Predictive maintenance has become indispensable in the oil and gas industry, serving as a pivotal strategy to uphold operational efficiency and preserve asset integrity. This paper delves into the profound impact of artificial intelligence (AI) technologies on predictive maintenance, ushering in a new era of proactive equipment management. By harnessing AI capabilities, oil and gas companies can preempt equipment failures, curtail downtime, and refine maintenance protocols, thereby optimizing overall operational performance. The integration of AI in predictive maintenance marks a paradigm shift, offering a proactive approach to asset management. Leveraging AI-driven analytics and real-time data monitoring, oil and gas facilities can fortify their asset integrity management practices. Through predictive algorithms and machine learning models, these technologies empower companies to forecast equipment malfunctions with unprecedented accuracy, allowing for timely interventions and mitigating potential risks the benefits of AI-powered predictive maintenance in the oil and gas sector are multifaceted the future of predictive maintenance in the oil and gas industry is brimming with promise. As AI technologies continue to evolve, we can anticipate further advancements in predictive analytics, fault detection, and decision support systems. By embracing innovation and collaboration, oil and gas companies can harness the full potential of AI-driven predictive maintenance, cementing their position as industry leaders in asset management and operational efficiency.
 
Keywords: 
Predictive Maintenance; Oil and Gas Facilities; AI (Artificial Intelligence); Asset Integrity Management; Condition Monitoring; Reliability Engineering
 
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