Mohammed Hazique Shaikh,
- Graduate Student and Senior Future Offer Manager, MS Engineering Management, Northeastern University and Industrial Automation Division, Schneider Electric, Foxboro, Massachusetts, USA
Abstract
Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to predict maintenance needs and minimise equipment downtime. These are not pilot projects. They are production deployments at the scale of the world’s largest energy companies, and they are changing what it means to operate an upstream or downstream oil and gas facility. This review paper examines the major AI application categories in oil and gas — predictive maintenance, drilling optimisation, reservoir characterisation, pipeline integrity, and process optimisation — and analyses the role of edge computing as the enabling infrastructure that makes real-time AI inference viable in remote, bandwidth-constrained, and operationally sensitive upstream and midstream environments. An original AI-Edge Deployment Matrix (AEDM) is proposed, providing a structured framework for matching AI use cases to the appropriate deployment architecture across the cloud-edge-field continuum. The AI in oil and gas market, valued at USD 5.31 billion in 2024, is projected to nearly triple USD 15.01 billion by 2029.
Keywords: Artificial intelligence, oil and gas, edge computing, predictive maintenance, drilling optimisation, reservoir characterisation, AI-Edge deployment matrix, AEDM, IIoT, digital twin, upstream, downstream
[This article belongs to Journal of Petroleum Engineering & Technology ]
Mohammed Hazique Shaikh. Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities. Journal of Petroleum Engineering & Technology. 2026; 16(02):01-06.
Mohammed Hazique Shaikh. Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities. Journal of Petroleum Engineering & Technology. 2026; 16(02):01-06. Available from: https://journals.stmjournals.com/jopet/article=2026/view=246916
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Journal of Petroleum Engineering & Technology
| Volume | 16 |
| Issue | 02 |
| Received | 30/04/2026 |
| Accepted | 22/05/2026 |
| Published | 15/06/2026 |
| Publication Time | 46 Days |
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