Adaptive Pressure Management and Plume Control in Geological Co2 Storage: Designing a Brine Extraction Field Experiment

Industrial scale injection of CO2 into the subsurface can result in significant fluid pressure increases, which can lead to potential environmental impacts such as caprock fracturing, fault activation and leakage into underground fresh water aquifers. Pressure management through brine extraction is an approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. However, the handling and management of the extracted brine has a cost that is added to carbon capture and sequestration (CCS) operations; therefore minimizing the extracted volume of brine can be of great importance. At the same time, economics of pressure management via brine extraction can be improved by treating the extracted high-salinity water and making it available for beneficial uses, for example as cooling water for power plants. In this paper, we introduce and demonstrate application of an adaptive reservoir management approach that optimizes extraction rates of reservoir brines for pressure control in an integrated optimization framework. Our approach will be tested during a brine extraction field experiment located in the southern United States, which is currently in the design and planning stages. The objective of the experiment is to evaluate the technical feasibility of managing subsurface pressures associated with large-scale CO2 injection volumes and to assess the cost and effectiveness of desalination technologies for saline waters containing high total dissolved solids (TDS). Our integrated adaptive management approach involves monitoring, model calibration, and optimization of brine extraction for pressure control. Based on measurements obtained during the injection phase and utilizing improved predictive models from repeated calibration, initial optimization calculations will be revised in regular intervals and the operating decisions for controlling and managing subsurface pressurization will be updated. In this paper, in preparation of the actual field demonstration, we investigate use of borehole measurements (i.e., pressure changes) and electromagnetic (EM) geophysical methods (i.e. salinity changes) in the adaptive management of the injection and brine extraction project. We also present a numerical exercise to investigate how the optimization performance is affected by the quality of initial site characterization data and by the frequency of dynamic model updates with newly acquired data during the injection. Our numerical study shows that more accurate initial reservoir characterization data reduce the risk of pressure buildup above a given maximum pressure because the optimization algorithm arrives at better estimates of initial extraction rates, which in turn results in better control of pressure during the overall injection times. Results also show that low frequencies of 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 proposed. 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. This will be demonstrated in the actual field study, with injection planned to start in early 2019.