Nonlinearly preconditioned constraint-preserving algorithms for subsurface three-phase flow with capillarity
KAUST DepartmentEarth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Embargo End Date2022-05-29
Permanent link to this recordhttp://hdl.handle.net/10754/662982
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AbstractThe multiphase flow model has been extensively used to describe complicated flow behaviors in subsurface formations, together with sophisticated reservoir models and well-defined fluid property. In this study, the fully implicit method, as one of most promising schemes for subsurface flow modeling, is employed to solve multiphase flow problems. In contrast to the conventional approach where mathematical models often include a pressure equation, the multiphase flow problems are modeled by up to three continuity equations so that mass conservation holds for all present phases. Another challenge that frequently shows up is the computed solution may sit outside its physically meaningful range, thereby leading to inaccurate predictions or even a failure of the simulation process. A simple remedy is to apply a cutting-off operation to the out-of-bound solution but such an action could ruin both local and global mass conservation. Instead, we replace the original model by a variational inequality formulation with box inequality constraints to protect the boundedness requirement on pressure and saturations from being violated. The variational inequality problem is then solved by a well-designed nonlinear solver consisting of the active-set reduced-space method and the nonlinear elimination preconditioning technique. A number of examples are presented to demonstrate that the proposed formulation is bound-preserving and mass-conservative for each of the present phases/components.
CitationYang, H., Li, Y., & Sun, S. (2020). Nonlinearly preconditioned constraint-preserving algorithms for subsurface three-phase flow with capillarity. Computer Methods in Applied Mechanics and Engineering, 367, 113140. doi:10.1016/j.cma.2020.113140
SponsorsThe authors would like to express their appreciations to the anonymous reviewer for the invaluable comments that have greatly improved the quality of the manuscript. This work is partially supported by the National Natural Science Foundation of China (No. 11971006, 11871069 and 51874262). The authors also greatly thank for the support from King Abdullah University of Science and Technology (KAUST), Saudi Arabia through the grants BAS/1/1351-01, REP/1/2879-01, and URF/1/3769-01. The first author was also supported in part by the PetroChina Innovation Foundation (2019D-5007-0213).