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Continuum reconstruction of the pore scale microstructure for Fontainebleau sandstone

Author

Listed:
  • Latief, F.D.E.
  • Biswal, B.
  • Fauzi, U.
  • Hilfer, R.

Abstract

A stochastic geometrical modeling technique is used to reconstruct a laboratory scale Fontainebleau sandstone with a sidelength of 1.5 cm. The model reconstruction is based on crystallite properties and diagenetic parameters determined from two-dimensional images. The three-dimensional pore scale microstructure of the sandstone is represented by a list of quartz crystallites defined geometrically and placed in the continuum. This allows generation of synthetic μ-CT images of the rock model at arbitrary resolutions. Quantitative microstructure comparison based on Minkowski functionals, two-point correlation function and local porosity theory indicates that this modeling technique can provide more realistic and accurate models of sandstones than many existing techniques used currently. Synthetic μ-CTimages at different resolutions from a laboratory scale model of Fontainebleau sandstone are made available to the scientific community for resolution dependent petrophysical analysis.

Suggested Citation

  • Latief, F.D.E. & Biswal, B. & Fauzi, U. & Hilfer, R., 2010. "Continuum reconstruction of the pore scale microstructure for Fontainebleau sandstone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1607-1618.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:8:p:1607-1618
    DOI: 10.1016/j.physa.2009.12.006
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    References listed on IDEAS

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    1. Biswal, B. & Manwart, C. & Hilfer, R., 1998. "Three-dimensional local porosity analysis of porous media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 255(3), pages 221-241.
    2. Biswal, B. & Manwart, C. & Hilfer, R. & Bakke, S. & Øren, P.E., 1999. "Quantitative analysis of experimental and synthetic microstructures for sedimentary rock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 273(3), pages 452-475.
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    Citations

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    Cited by:

    1. Chen, DongDong & Liu, Yang & Wang, XiaoRui & Wang, Mei, 2022. "Reconstruction of the microstructure based on hierarchical simulated annealing with erosion method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Zou, Xiaojing & He, Changyu & Guan, Wei & Zhou, Yan & Zhao, Hongyang & Cai, Mingyu, 2023. "Reservoir tortuosity prediction: Coupling stochastic generation of porous media and machine learning," Energy, Elsevier, vol. 285(C).
    3. Chen, Dongdong & He, Xiaohai & Teng, Qizhi & Xu, Zhi & Li, Zhengji, 2014. "Reconstruction of multiphase microstructure based on statistical descriptors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 240-250.
    4. Wang, Yuzhu & Rahman, Sheik S. & Arns, Christoph H., 2018. "Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 177-188.

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