Simulation of CO2 Sequestration at Rock Spring Uplift, Wyoming
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Release | : 2011 |
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Many geological, geochemical, geomechanical and hydrogeological factors control CO2 storage in subsurface. Among them heterogeneity in saline aquifer can seriously influence design of injection wells, CO2 injection rate, CO2 plume migration, storage capacity, and potential leakage and risk assessment. This study applies indicator geostatistics, transition probability and Markov chain model at the Rock Springs Uplift, Wyoming generating facies-based heterogeneous fields for porosity and permeability in target saline aquifer (Pennsylvanian Weber sandstone) and surrounding rocks (Phosphoria, Madison and cap-rock Chugwater). A multiphase flow simulator FEHM is then used to model injection of CO2 into the target saline aquifer involving field-scale heterogeneity. The results reveal that (1) CO2 injection rates in different injection wells significantly change with local permeability distributions; (2) brine production rates in different pumping wells are also significantly impacted by the spatial heterogeneity in permeability; (3) liquid pressure evolution during and after CO2 injection in saline aquifer varies greatly for different realizations of random permeability fields, and this has potential important effects on hydraulic fracturing of the reservoir rock, reactivation of pre-existing faults and the integrity of the cap-rock; (4) CO2 storage capacity estimate for Rock Springs Uplift is 6614 ± 256 Mt at 95% confidence interval, which is about 36% of previous estimate based on homogeneous and isotropic storage formation; (5) density profiles show that the density of injected CO2 below 3 km is close to that of the ambient brine with given geothermal gradient and brine concentration, which indicates CO2 plume can sink to the deep before reaching thermal equilibrium with brine. Finally, we present uncertainty analysis of CO2 leakage into overlying formations due to heterogeneity in both the target saline aquifer and surrounding formations. This uncertainty in leakage will be used to feed into risk assessment modeling.