SR-02Frontier
Automated History Matching
Tunes the reservoir model until it reproduces what the field actually produced, automatically and with the uncertainty kept rather than discarded.
Subsurface & Reservoir IntelligenceAIDomain
SR-01FrontierWave 3AIDomain
Smart Proxy Reservoir Simulation
In one sentence
A learned stand-in for the full reservoir simulator that answers in seconds instead of hours, so an engineer can test fifty scenarios instead of three.
The problem
A full-physics run on a multi-million-cell model takes six to thirty hours. Optimisation, uncertainty quantification and history matching all need hundreds of runs, so in practice they are replaced by a handful of hand-picked cases and engineering judgement.
How it works
A neural surrogate is trained on a designed ensemble of full-physics runs, learning the mapping from control and property inputs to pressure and saturation response. It is used only inside the training envelope, and every proxy answer that drives a decision is confirmed with one full-physics run before it leaves the team.
Data required
- A validated full-physics simulation deck for the field
- Compute budget for 200–500 training runs of that deck
- Historical production and injection by well
- Property model realisations covering the intended uncertainty range
What you get
- Sub-second forecast of field and well response to a control scenario
- Uncertainty envelope across the property ensemble
- Ranked scenario table for the reservoir management meeting
What it cannot do
A proxy cannot extrapolate. Outside the range of controls and properties it was trained on it fails quietly rather than loudly, which is the dangerous failure mode, so the system refuses queries outside the training hull instead of answering them. It also needs an existing trustworthy simulation deck — it does not replace building one.
Every capability page states a real limitation. If a vendor cannot tell you where their product stops, you are not being told the truth about where it starts.
Related capabilities
- SR-11Intermediate
Forecasting with Uncertainty
Produces P10, P50 and P90 production forecasts whose spread is calculated, not chosen to look reasonable.
Subsurface & Reservoir IntelligenceAI - SR-08Frontier
EOR/IOR Strategy Optimization
Searches injection strategies — what to inject, where, and at what rate — against recovery and cost together.
Subsurface & Reservoir IntelligenceAIDomain - SR-10Frontier
Development Well Placement
Searches for where the next wells should go, with drilling feasibility and surface constraints inside the search rather than applied afterwards.
Subsurface & Reservoir IntelligenceAIDomain - SR-05Frontier
Generative Inter-Well Modeling
Fills the rock between wells with geologically plausible detail instead of a smooth interpolation that no outcrop ever looked like.
Subsurface & Reservoir IntelligenceAI