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      Acceleration of Gas Reservoir Simulation Using Proper Orthogonal Decomposition

      , ,
      Geofluids
      Hindawi Limited

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          Abstract

          High-precision and high-speed reservoir simulation is important in engineering. Proper orthogonal decomposition (POD) is introduced to accelerate the reservoir simulation of gas flow in single-continuum porous media via establishing a reduced-order model by POD combined with Galerkin projection. Determination of the optimal mode number in the reduced-order model is discussed to ensure high-precision reconstruction with large acceleration. The typical POD model can achieve high precision for both ideal gas and real gas using only 10 POD modes. However, acceleration of computation can only be achieved for ideal gas. The obstacle of POD acceleration for real gas is that the computational time is mainly occupied by the equation of state (EOS). An approximation method is proposed to largely promote the computational speed of the POD model for real gas flow without decreasing the precision. The improved POD model shows much higher acceleration of computation with high precision for different reservoirs and different pressures. It is confirmed that the acceleration of the real gas reservoir simulation should use the approximation method instead of the computation of EOS.

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          Direct simulations of two-phase flow on micro-CT images of porous media and upscaling of pore-scale forces

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            Compositional modeling of three-phase flow with gravity using higher-order finite element methods

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              Mode decomposition methods for flows in high-contrast porous media. Global–local approach

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                Author and article information

                Journal
                Geofluids
                Geofluids
                Hindawi Limited
                1468-8115
                1468-8123
                2018
                2018
                : 2018
                :
                : 1-15
                Article
                10.1155/2018/8482352
                5727d9bd-7277-4ae7-b51c-f4352628d866
                © 2018

                http://creativecommons.org/licenses/by/4.0/

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