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
PR-11IntermediateWave 2AIDomain
Waterflood & Produced Water Management
In one sentence
Works out which injector is actually supporting which producer, and where the injected water is being wasted.
The problem
Injection is allocated by pattern geometry drawn on a map, but real connectivity follows faults and high-permeability streaks. Water is routinely injected into wells that support nothing, at a real cost in power, chemicals and disposal.
How it works
Capacitance-resistance modelling and signal correlation between injection and production rates infer inter-well connectivity from the production data itself, independently of the geomodel. Voidage replacement is tracked by pattern and the results are reconciled against tracer surveys where they exist.
Data required
- Injection rates and pressures by well, daily where possible
- Production rates with water cut by well
- Well locations, completions and perforated intervals
- Any inter-well tracer survey results
What you get
- Inter-well connectivity map with injector-producer allocation fractions
- Voidage replacement ratio by pattern with trend
- Ranked list of injectors with low or negative measured contribution
What it cannot do
Capacitance-resistance modelling needs rate variation to infer connectivity. In a field operated at steady rates for years, the signal is too weak and the method returns connectivity estimates with confidence intervals wide enough to be useless — in which case the honest recommendation is a designed rate-perturbation test, not a longer analysis.
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.
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