SOR
BEFORE AI 8.1 t/t
7.2 t/t
AFTER AI
Feature 11 · CSS + SRP Joint Optimization · Well B-12 · DEMO MODE
STEAM-OIL RATIO & ENERGY OPTIMIZATION
Business KPI decision layer that connects CSS heating and SRP speed parameters to representative steam use, energy intensity, production and equipment stress.
Overall AI recommendation
Adjust SRP speed to reduce energy and equipment stress.
The joint model uses CSS steam volume, soak time and injection pressure with SRP speed and VFD frequency—not isolated equipment settings—to protect production while reducing resource intensity.
Steam saving
11.7%
Stress reduction
42.6%
Business KPI dashboard
BEFORE AI vs AFTER AI
↓ 11.1%
Energy / barrel
BEFORE AI 523 kWh/bbl
495 kWh/bbl
AFTER AI
Steam consumption
BEFORE AI 300 t/cycle
265 t/cycle
AFTER AI
Oil production
BEFORE AI 40 m³/day
39.8 m³/day
AFTER AI
Optimization impact comparison
Production is scaled ×10 in this chart only so the before/after direction remains visible alongside energy and steam.
Before AIAfter AI
- Before AI
- After AI
AI optimized control plan
Steam300 → 265 t/cycle
Soak18 → 20 hours
Injection pressure25 → 25 bar
SRP speed5.8 → 5.0 SPM
VFD43 → 41 Hz
Stores the recommendation locally and publishes it to the prototype realtime channel when available. Field execution requires approval.
SOR reduction
11.1%
Lower steam per tonne of produced oil
Energy reduction
5.4%
Lower lift and steam-system energy per barrel
Production impact
-0.5%
Predicted optimized production: 39.8 m³/day
Explainable joint optimization
Why this operating point is recommended
01
CSS thermal response is sufficient to reduce steam volume while holding the soak window.
02
SRP speed above the stable operating setpoint increases energy draw and dynamic rod loading.
03
Joint CSS + SRP optimization targets lower SOR without sacrificing representative production.