14–17 May 2018
New Orleans
US/Central timezone

Session

Parallel 3-G

Parallel 3-G
15 May 2018, 09:30
New Orleans

New Orleans

Presentation materials

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  1. Prof. Hamdi Tchelepi (Stanford University)
    15/05/2018, 09:32
    MS 2.10: Advanced finite-volume methods for flow and transport in porous media
    Oral 20 Minutes

    We propose a novel finite volume method for anisotropic linear elasticity problem. The derivation of the flux approximation method for elasticity problem closely follows our previous work [1] on the nonlinear finite volume methods for diffusion equation featuring positivity and discrete maximum principles. It is based on the extensions of the harmonic point idea of [2] from the scalar to...

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  2. Ivan Yotov (University of Pittsburgh)
    15/05/2018, 09:50
    MS 2.10: Advanced finite-volume methods for flow and transport in porous media
    Oral 20 Minutes

    We develop higher order multipoint flux mixed finite element (MFMFE) methods for solving elliptic problems on quadrilateral and hexahedral grids that reduce to cell-based pressure systems. The methods are based on a new family of mixed finite elements, which are enhanced Raviart-Thomas spaces with bubbles that are curls of specially chosen polynomials. The velocity degrees of freedom of the...

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  3. Dr Martin A. Diaz-Viera (INSTITUTO MEXICANO DEL PETROLEO)
    15/05/2018, 10:08
    MS 2.10: Advanced finite-volume methods for flow and transport in porous media
    Oral 20 Minutes

    In this work a general model of multiphase flow and multicomponent transport in porous media to simulate, analyze and interpret hydrocarbon recovery processes by injecting low salinity water using open source software is presented. The flow model is multiphase considering capillary pressure and relative permeabilities depending on salinity, while the transport model is multicomponent and...

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  4. Dr Olav Møyner (SINTEF, NTNU)
    15/05/2018, 10:26
    MS 2.10: Advanced finite-volume methods for flow and transport in porous media
    Oral 20 Minutes

    CO$_2$ capture and storage is an important technology for mitigating climate change. Design of efficient strategies for safe, long-term storage requires the capability to efficiently simulate processes taking place on very different temporal and spatial scales. The physical laws describing CO$_2$ storage are the same as for hydrocarbon recovery, but the characteristic spatial and temporal...

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