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    Modeling of 3D Rock Porous Media by Combining X-Ray CT and Markov Chain Monte Carlo

    Source: Journal of Energy Resources Technology:;2020:;volume( 142 ):;issue: 001::page 013001-1
    Author:
    Lin, Wei
    ,
    Li, Xizhe
    ,
    Yang, Zhengming
    ,
    Xiong, Shengchun
    ,
    Luo, Yutian
    ,
    Zhao, Xinli
    DOI: 10.1115/1.4045461
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Rocks contain multi-scale pore structures, with dimensions ranging from nano- to sample-scale, the inherent tradeoff between imaging resolution and sample size limits the simultaneous characterization of macro-pores and micro-pores using single-resolution imaging. Here, we developed a new hybrid digital rock modeling approach to cope with this open challenge. We first used micron-CT to construct the 3D macro-pore digital rock of tight sandstone, then performed high-resolution SEM on the three orthogonal surfaces of sandstone sample, thus reconstructed the 3D micro-pore digital rock by Markov chain Monte Carlo (MCMC) method; finally, we superimposed the macro-pore and micro-pore digital rocks to achieve the integrated digital rock. Maximal ball algorithm was used to extract pore-network parameters of digital rocks, and numerical simulations were completed with Lattice-Boltzmann method (LBM). The results indicate that the integrated digital rock has anisotropy and good connectivity comparable with the real rock, and porosity, pore-throat parameters and intrinsic permeability from simulations agree well with the values acquired from experiments. In addition, the proposed approach improves the accuracy and scale of digital rock modeling and can deal with heterogeneous porous media with multi-scale pore-throat system.
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      Modeling of 3D Rock Porous Media by Combining X-Ray CT and Markov Chain Monte Carlo

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    contributor authorLin, Wei
    contributor authorLi, Xizhe
    contributor authorYang, Zhengming
    contributor authorXiong, Shengchun
    contributor authorLuo, Yutian
    contributor authorZhao, Xinli
    date accessioned2022-02-04T22:57:11Z
    date available2022-02-04T22:57:11Z
    date copyright1/1/2020 12:00:00 AM
    date issued2020
    identifier issn0195-0738
    identifier otherjert_142_1_013001.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4275780
    description abstractRocks contain multi-scale pore structures, with dimensions ranging from nano- to sample-scale, the inherent tradeoff between imaging resolution and sample size limits the simultaneous characterization of macro-pores and micro-pores using single-resolution imaging. Here, we developed a new hybrid digital rock modeling approach to cope with this open challenge. We first used micron-CT to construct the 3D macro-pore digital rock of tight sandstone, then performed high-resolution SEM on the three orthogonal surfaces of sandstone sample, thus reconstructed the 3D micro-pore digital rock by Markov chain Monte Carlo (MCMC) method; finally, we superimposed the macro-pore and micro-pore digital rocks to achieve the integrated digital rock. Maximal ball algorithm was used to extract pore-network parameters of digital rocks, and numerical simulations were completed with Lattice-Boltzmann method (LBM). The results indicate that the integrated digital rock has anisotropy and good connectivity comparable with the real rock, and porosity, pore-throat parameters and intrinsic permeability from simulations agree well with the values acquired from experiments. In addition, the proposed approach improves the accuracy and scale of digital rock modeling and can deal with heterogeneous porous media with multi-scale pore-throat system.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleModeling of 3D Rock Porous Media by Combining X-Ray CT and Markov Chain Monte Carlo
    typeJournal Paper
    journal volume142
    journal issue1
    journal titleJournal of Energy Resources Technology
    identifier doi10.1115/1.4045461
    journal fristpage013001-1
    journal lastpage013001-8
    page8
    treeJournal of Energy Resources Technology:;2020:;volume( 142 ):;issue: 001
    contenttypeFulltext
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