Integrating artificial intelligence into engineering processes for improved efficiency and safety in oil and gas operations
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, Nigeria.
Review
Open Access Research Journal of Engineering and Technology, 2024, 06(01), 039–051.
Article DOI: 10.53022/oarjet.2024.6.1.0012
Publication history:
Received on 06 February 2024; revised on 12 March 2024; accepted on 15 March 2024
Abstract:
This paper delves into the significance, challenges, and potential of AI applications within the oil and gas sector. In the dynamic landscape of oil and gas operations, efficiency and safety stand as paramount concerns. Traditional engineering processes, while robust, often face limitations in adapting to the evolving complexities of the industry. However, the advent of AI technologies offers a paradigm shift, presenting unprecedented opportunities for optimization and risk mitigation. This paper explores the multifaceted role of AI in engineering processes throughout the oil and gas value chain. It examines how AI, encompassing machine learning, deep learning, and predictive analytics, empowers decision-makers with real-time insights, optimizing exploration, production, transportation, and refining processes. Efficiency gains are witnessed through predictive maintenance strategies, enabling proactive asset management and minimizing downtime. Additionally, AI-driven process optimization techniques enhance resource allocation, streamlining operations and maximizing output while reducing costs. Moreover, AI's integration fosters a culture of safety by augmenting risk assessment and hazard identification capabilities. Through advanced algorithms, AI systems analyze vast datasets to detect anomalies and predict potential safety hazards, enabling proactive intervention and accident prevention. However, the journey towards AI integration is not without challenges. Technical complexities, regulatory frameworks, and cyber security concerns pose significant hurdles that require careful navigation. Moreover, ethical considerations surrounding data privacy and algorithmic bias necessitate robust governance frameworks to ensure responsible AI deployment. Looking ahead, the paper delineates future trends and opportunities in AI adoption within the oil and gas sector. It underscores the potential for continued innovation and disruption, reshaping workforce dynamics and skill requirements. Embracing AI not only drives operational excellence but also propels the industry towards a sustainable and resilient future
Keywords:
Artificial Intelligence (AI); Engineering Processes; Efficiency Improvement; Safety Enhancement; Oil and Gas Operations; Integration Challenges
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0