A facies-constrained flow-network model for fast history matching and production optimization of polymer flooding reservoirs
Petroleum Science, 23(6):3408 - 3438, 2026.
Summary
This work introduces a flow-network model that incorporates sedimentary facies information to accelerate history matching and polymer-flooding optimization. The model extends GPSNet by representing connections between wells with one-dimensional discretized grids while preserving facies boundaries identified using edge detection and level-set methods. Grid properties are assigned and calibrated according to the resulting facies regions, giving the simplified network geological constraints that its predecessor lacks. History matching uses an ensemble smoother with multiple data assimilation, and production controls are optimized with differential evolution. Numerical examples compare the facies-constrained model with the original network approach. The reported improvements concern predictive accuracy, reliability, and reduced ambiguity in history matching. The method is intended to support repeated, rapid simulations in closed-loop reservoir management, where geological consistency must be balanced with the computational demands of updating models and choosing operating strategies.