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Probabilistic modeling and global sensitivity analysis for CO2 storage in geological formations: a spectral approach
Institution:1. Division of Computer, Electrical and Mathematical Sciences & Engineering, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal 23955–6900, Kingdom of Saudi Arabia;2. The Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA;3. Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA;4. Département de mathématiques et de génie industriel, École Polytechnique de Montréal, C.P. 6079, succ. Centre-ville, Montréal, Québec, Canada, H3C 3A7;5. Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA
Abstract:This work focuses on the simulation of CO2 storage in deep underground formations under uncertainty and seeks to understand the impact of uncertainties in reservoir properties on CO2 leakage. To simulate the process, a non-isothermal two-phase two-component flow system with equilibrium phase exchange is used. Since model evaluations are computationally intensive, instead of traditional Monte Carlo methods, we rely on polynomial chaos (PC) expansions for representation of the stochastic model response. A non-intrusive approach is used to determine the PC coefficients. We establish the accuracy of the PC representations within a reasonable error threshold through systematic convergence studies. In addition to characterizing the distributions of model observables, we compute probabilities of excess CO2 leakage. Moreover, we consider the injection rate as a design parameter and compute an optimum injection rate that ensures that the risk of excess pressure buildup at the leaky well remains below acceptable levels. We also provide a comprehensive analysis of sensitivities of CO2 leakage, where we compute the contributions of the random parameters, and their interactions, to the variance by computing first, second, and total order Sobol’ indices.
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