POD-Galerkin Model for Incompressible Single-Phase Flow in Porous Media

Yi Wang; Bo Yu; Shuyu Sun

doi:10.1515/phys-2016-0061

POD-Galerkin Model for Incompressible Single-Phase Flow in Porous Media

Yi Wang, Bo Yu, Shuyu Sun

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Fast prediction modeling via proper orthogonal decomposition method combined with Galerkin projection is applied to incompressible single-phase fluid flow in porous media. Cases for different configurations of porous media, boundary conditions and problem scales are designed to examine the fidelity and robustness of the model. High precision (relative deviation 1.0 x 10(-4)% similar to 2.3 x 10(-1)%) and large acceleration (speed-up 880 similar to 98454 times) of POD model are found in these cases. Moreover, the computational time of POD model is quite insensitive to the complexity of problems. These results indicate POD model is especially suitable for large-scale complex problems in engineering.

Original language	English (US)
Pages (from-to)	588-601
Number of pages	14
Journal	Open Physics
Volume	14
Issue number	1
DOIs	https://doi.org/10.1515/phys-2016-0061
State	Published - Jan 25 2017

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https://repository.kaust.edu.sa/bitstream/10754/623718/1/%5bOpen%20Physics%5d%20POD-Galerkin%20Model%20for%20Incompressible%20Single-Phase%20Flow%20in%20Porous%20Media.pdf

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title = "POD-Galerkin Model for Incompressible Single-Phase Flow in Porous Media",

abstract = "Fast prediction modeling via proper orthogonal decomposition method combined with Galerkin projection is applied to incompressible single-phase fluid flow in porous media. Cases for different configurations of porous media, boundary conditions and problem scales are designed to examine the fidelity and robustness of the model. High precision (relative deviation 1.0 x 10(-4)% similar to 2.3 x 10(-1)%) and large acceleration (speed-up 880 similar to 98454 times) of POD model are found in these cases. Moreover, the computational time of POD model is quite insensitive to the complexity of problems. These results indicate POD model is especially suitable for large-scale complex problems in engineering.",

author = "Yi Wang and Bo Yu and Shuyu Sun",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): BAS/1/1351-01-01 Acknowledgements: The work presented in this paper has been supported by National Natural Science Foundation of China (NSFC) (No. 51576210, No. 51476073, No. 51325603), Science Foundation of China University of Petroleum-Beijing (No. 2462015BJB03, No. 2462015YQ0409, No. C201602) and also supported in part by funding from King Abdullah University of Science and Technology (KAUST) through the grant BAS/1/1351-01-01.",

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doi = "10.1515/phys-2016-0061",

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AU - Wang, Yi

AU - Yu, Bo

AU - Sun, Shuyu

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): BAS/1/1351-01-01 Acknowledgements: The work presented in this paper has been supported by National Natural Science Foundation of China (NSFC) (No. 51576210, No. 51476073, No. 51325603), Science Foundation of China University of Petroleum-Beijing (No. 2462015BJB03, No. 2462015YQ0409, No. C201602) and also supported in part by funding from King Abdullah University of Science and Technology (KAUST) through the grant BAS/1/1351-01-01.

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N2 - Fast prediction modeling via proper orthogonal decomposition method combined with Galerkin projection is applied to incompressible single-phase fluid flow in porous media. Cases for different configurations of porous media, boundary conditions and problem scales are designed to examine the fidelity and robustness of the model. High precision (relative deviation 1.0 x 10(-4)% similar to 2.3 x 10(-1)%) and large acceleration (speed-up 880 similar to 98454 times) of POD model are found in these cases. Moreover, the computational time of POD model is quite insensitive to the complexity of problems. These results indicate POD model is especially suitable for large-scale complex problems in engineering.

AB - Fast prediction modeling via proper orthogonal decomposition method combined with Galerkin projection is applied to incompressible single-phase fluid flow in porous media. Cases for different configurations of porous media, boundary conditions and problem scales are designed to examine the fidelity and robustness of the model. High precision (relative deviation 1.0 x 10(-4)% similar to 2.3 x 10(-1)%) and large acceleration (speed-up 880 similar to 98454 times) of POD model are found in these cases. Moreover, the computational time of POD model is quite insensitive to the complexity of problems. These results indicate POD model is especially suitable for large-scale complex problems in engineering.

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POD-Galerkin Model for Incompressible Single-Phase Flow in Porous Media

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