Pore-Space-Aware CO2-EOR Forecast and Optimization Using DMDc-Accelerated Surrogate Modeling: A SACROC Field Case

Abstract CO2-enhanced oil recovery (CO2-EOR) operations are increasingly recognized as viable carbon storage projects in the push toward net-zero emissions. Optimizing these projects requires balancing oil production with secure CO2 storage, especially as new incentives (e.g. 45Q tax credits) reward stored CO2. This study integrates a pore-space-aware CO2 storage optimization model with dynamic mode decomposition with control (DMDc) surrogate modeling to optimize full-field CO2-EOR in the Scurry