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Energy: Oil & Gas AI Strategy: opportunities, use cases & the operating model
AI value lies in reservoir characterisation, production optimisation, and HSE risk reduction, turning seismic, downhole, and equipment data into recoverable barrels and fewer incidents rather than dashboards.
Where AI creates value
Reservoir characterisationSeismic interpretation and subsurface modelling at scale
Production optimisationWell and lift performance tuned for output
Predictive equipment integrityRotating asset and pipeline failure prediction
HSE and emissionsMethane leak detection and incident prevention
Drilling optimisationReal-time rate-of-penetration and hazard avoidance
Trading and supplyCommodity and logistics forecasting for margin
Top AI use cases
- Seismic image interpretation accelerating prospect identification and de-risking
- Production optimisation adjusting choke and lift across well portfolios
- Methane and flare emissions detection from satellite and sensor imagery
- Predictive integrity monitoring of pipelines, compressors, and pumps
- Drilling advisory systems reducing non-productive time and stuck-pipe events
What has to change (operating model)
- OT cybersecurity hardening as AI connects to SCADA and control systems
- Emissions and methane reporting governance tied to model-derived measurements
- Subsurface data liberation from siloed vendor and partner formats
- HSE accountability frameworks for AI-assisted operational decisions
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