UC-199
Group Reservoir Surveillance Digital Twin
AI-powered reservoir surveillance continuously monitors production and subsurface data, detects deviations from reservoir forecasts, and recommends timely interventions to maximize recovery, improve forecast accuracy, and optimize asset performance
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The Challenge
Reservoir surveillance runs differently across two portfolios, and forecast drift is found at the annual review. By then the intervention window has often closed.
How It Works
- Ingests production, pressure and injection data with reservoir models.
- ML learns expected behaviour and flags divergence per well and reservoir.
- Alerts subsurface teams with ranked intervention candidates.
What It Removes
- Drift found at the annual review
- Surveillance craft siloed by portfolio
- Intervention windows missed
Input Data RequirementsProduction/pressure/injection histories, reservoir models, well events
Output FormatLive divergence alerts, ranked intervention candidates, surveillance dashboards
“Every reservoir watched the same way - drift flagged while acting is still cheap.”