Understanding Subsurface Uncertainty for Carbon Storage in Saline Aquifers: PVT, SCAL, and Grid-Size Sensitivity

Abstract

Abstract Subsurface uncertainty has a great deal of impact on the development of oil and gas reservoirs, as demonstrated through decades of industry experience. Understanding uncertainty to facilitate robust business decisions across potential scenarios is the cornerstone of successful field development. Although carbon storage is also subject to subsurface uncertainty, the phenomena that impact storage efficiency may not be the same as those influencing oil and gas production. The objectives of this study are to utilize reservoir simulation to Investigate how rock and fluid properties affect CO2 plume size, migration, and trapping mechanisms during- and post-injection, Perform grid size sensitivity to define resolution requirements, and Quantify the impacts of coarse simulation grid and the requirements of monitoring resolution. We present how reservoir conditions (i.e., temperature, pressure, and salinity) affect fluid properties and carbon storage performance. Reservoir temperature and pressure are considered both independently and together along geothermal gradients. A similar investigation also provides the sensitivity result based on varying SCAL (i.e., relative permeability and capillary pressure) parameters. For the grid size sensitivity, the findings demonstrate that an accurate plume size requires a fine vertical grid resolution, while the areal grid resolution impacts the dissolution rate. We make gridding scheme recommendations for reliable predictions based on these findings. We also analyze the result to quantify the error due to coarser grid size and the requirements for appropriate monitoring resolutions. The results from the sensitivity study can help categorize storage site potential. The grid size study provides crucial information to develop reservoir simulation best practices in evaluating carbon storage candidates. Another aspect of a carbon storage operation is the monitoring plan to ensure the containment of the injected CO2. Since the geometry of the plume continues to evolve post-injection, the simulated predictions can guide the selection of monitoring technology with appropriate resolution necessary to capture the CO2 plume at various timeframes.