Adaptive Pressure Management in Geological CO2 Storage: Application to A Brine Extraction Field Experiment

Injection of CO₂ into the subsurface at industrial scale can lead to potential environmental impacts. Brine extraction is one approach for managing formation pressure and plume movement in response to CO₂ injection. In this study, we present application of an adaptive management approach that optimizes extraction rates of brine for pressure control in an integrated optimization framework. Our approach will be tested in a brine extraction field experiment located in the southern United States, which is currently in the design and planning stages. The project will involve fresh-water injection into a thin brine-bearing sandstone layer to create pressure increases that can be controlled and managed. A pressure management strategy will combine "active" extraction with optimized time-varying pumping rates and "passive" pressure relief, which relies on the pressure increase in the injection layer. Our integrated adaptive management approach involves hydrogeological and geophysical monitoring, model calibration, and optimization of brine extraction for pressure control. Based on monitoring data and utilizing improved predictive models from repeated calibration, optimization calculations and the operating decisions for controlling and managing subsurface pressurization will be updated. In preparation for the actual field demonstration, we are conducting a numerical exercise to investigate how the optimization performance is affected by the quality of initial site characterization data, the type and frequency of the monitoring data and the frequency of dynamic model updates with newly acquired data during the injection. Our numerical study shows that infrequent model calibration and optimization with the new data, especially at early injection periods, may lead to optimization problems, either because pressure buildup constraints are violated or excessively high extraction rates are required. These optimization problems can be eliminated if more frequent data collection and model calibration are conducted, especially at early injection times. Approaches such as adaptive pressure management may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the brine extraction volumes while controlling pressure buildups.