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Computational Modeling of the Geologic Sequestration of Carbon Dioxide
Citation:
Schnaar, G. AND D. C. DIGIULIO. Computational Modeling of the Geologic Sequestration of Carbon Dioxide . Vadose Zone Journal. Soil Science Society of America, Madison, WI, 08(2):389-403, (2009).
Impact/Purpose:
The objective is to demonstrate the possible need before the injection of CO2 operators of geologic sequestration projects may need to demonstrate the nonendangermet of groundwater resouces during the lifetime of the project.
Description:
Geologic sequestration of CO2 is a component of C capture and storage (CCS), an emerging technology for reducing CO2 emissions to the atmosphere, and involves injection of captured CO2 into deep subsurface formations. Similar to the injection of hazardous wastes, before injection of CO2, operators of geologic sequestration projects may need to demonstrate nonendangerment of groundwater resources during the lifetime of the project. Future requirements related to CO2 accounting and transfer credits may require operators to evaluate and quantify any surface releases. Subsurface fluid flow computational models have been advocated as an integral tool in predicting and tracking the migration of CO2 or mobilized constituents. Modeling the injection and sequestration of CO2 poses unique challenges, such as the need to properly characterize CO2 transport properties across a large range of temperatures and pressures, and the need to couple multiphase flow, reactive transport, and geomechanical processes. In addition, the volumes of CO2 that may be injected are largely unprecedented, and an appropriate amount of site characterization across the potentially impacted area will be difficult. In the last several years, there have been several research studies specifically modeling the problem of subsurface injection of CO2. Existing studies demonstrate the use of modeling in project design, site characterization, assessments of leakage, and site monitoring. Particularly informative components of existing modeling studies include parameter sensitivity analyses, evaluation of numerical artifacts, code comparison, and demonstrations of model calibration to site monitoring data.
