Evaluation of Uncertainty in CO2 Sequestration Modeling: a Flow Relevance Study using Experimental Stratigraphy and Field Verification (Teapot Dome, Wyoming)

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Evaluation of Uncertainty in CO2 Sequestration Modeling: a Flow Relevance Study using Experimental Stratigraphy and Field Verification (Teapot Dome, Wyoming)Ye ZhangEAR-0838250University of WyomingABSTRACTInjection of supercritical carbon dioxide (CO2) into deep permeable formations of sedimentary basins has been proposed as a viable approach to greenhouse gas sequestration (geostorage). Both aquifer storage efficiency and potential leakage subsequent to injection are critical factors for consideration. Though numerical modeling provides a key assessment tool, multiple sources of uncertainty exist in the model construct, creating significant uncertainty in predicting CO2 flow in the storage formations. For example, one important conceptual model uncertainty is the multiple levels of homogeneity with which a formation can be represented, which are typically constrained by the quality and accessibility of site-specific data. For a given model, some parameters exert more influence on the prediction outcomes than others, thus in site evaluations, the value and relevance of diverse data types need to be better understood. This proposal aims to address this fundamental assessment issue with a two-pronged strategy. First, CO2 flow simulations will be conducted in a novel, experiment-based synthetic aquifer as well as in three increasingly homogenized models (i.e., facies-scale, facies-assemblage-scale, formation scale representations). To assess parameter uncertainties, the simulations will be conducted within an efficient computation framework based on the Design of Experiment. By comparing model predictions (full range of scenarios) and sensitivity (the most significant parameters impacting CO2 flow), an optimal level of model complexity will be determined. The insights gained will then help guide the development of a site-specific model for a CO2 injection test in the Teapot Dome, Wyoming. In modeling the field test, the analysis workflow will be validated in a dynamic setting by integrating simulation with data collection and field observation. Results will clarify the most relevant data types in CO2 modeling that require better characterization. Since successful implementation of carbon geostorage depends on both the accuracy and cost-effectiveness of the technical assessment studies, our work will be of broad scientific significance as well as high societal relevance.