TY - JOUR
T1 - A probabilistic collocation Eulerian-Lagrangian localized adjoint method on sparse grids for assessing CO2 leakage through wells in randomly heterogeneous porous media
AU - Wang, Hong
AU - Ren, Yongqiang
AU - Jia, Jinhong
AU - Celia, Michael A.
N1 - Funding Information:
This work was supported in part by the National Science Foundation under Grants EAR-0934722 , EAR-0934747 , and DMS-1216923 , by the National Natural Science Foundation of China under Grants 91130010 and 11471194 , and by the State Scholarship Fund from China Scholarship Council (Nos. 201206220009 and 201306220110 ). The authors would like to express their sincere thanks to the referees for their very helpful comments and suggestions, which greatly improved the quality of this paper.
Publisher Copyright:
© 2014 Elsevier B.V.
PY - 2015/8/1
Y1 - 2015/8/1
N2 - We develop a probabilistic collocation Eulerian-Lagrangian localized adjoint method on sparse grids for assessing CO2 leakage through wells in randomly heterogeneous porous media, by utilizing the intrinsic mathematical, numerical, and physical properties of the mathematical model. We model the process in which CO2 is injected into a deep aquifer, spreads within the aquifer and, upon reaching a leaky well, rises up to a shallower aquifer, to quantify the leakage rate, which depends on the pressure build-up in the aquifer due to injection and the buoyancy of CO2. The underlying Eulerian-Lagrangian framework has high potential to improve the efficiency and accuracy for the numerical simulation of complex flow and transport processes in CO2 sequestration. The sparse grid probabilistic collocation framework adds computationally efficient uncertainty quantification functionality onto pre-existing Eulerian-Lagrangian methods in a nonintrusive manner. It also provides a scalable framework to consider uncertainty in a straightforward parallel manner. Preliminary numerical experiments show the feasibility and potential of the method.
AB - We develop a probabilistic collocation Eulerian-Lagrangian localized adjoint method on sparse grids for assessing CO2 leakage through wells in randomly heterogeneous porous media, by utilizing the intrinsic mathematical, numerical, and physical properties of the mathematical model. We model the process in which CO2 is injected into a deep aquifer, spreads within the aquifer and, upon reaching a leaky well, rises up to a shallower aquifer, to quantify the leakage rate, which depends on the pressure build-up in the aquifer due to injection and the buoyancy of CO2. The underlying Eulerian-Lagrangian framework has high potential to improve the efficiency and accuracy for the numerical simulation of complex flow and transport processes in CO2 sequestration. The sparse grid probabilistic collocation framework adds computationally efficient uncertainty quantification functionality onto pre-existing Eulerian-Lagrangian methods in a nonintrusive manner. It also provides a scalable framework to consider uncertainty in a straightforward parallel manner. Preliminary numerical experiments show the feasibility and potential of the method.
KW - CO sequestration and leakage
KW - Eulerian-Lagrangian method
KW - Heterogeneous porous media
KW - Probabilistic collocation method
KW - Risk assessment
KW - Uncertainty quantification
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U2 - 10.1016/j.cma.2014.11.034
DO - 10.1016/j.cma.2014.11.034
M3 - Article
AN - SCOPUS:84939991206
SN - 0045-7825
VL - 292
SP - 35
EP - 53
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
ER -