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Pore space morphology analysis using maximal inscribed spheres

Author

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  • Silin, Dmitriy
  • Patzek, Tad

Abstract

A new robust algorithm analyzing the geometry and connectivity of the pore space of sedimentary rock is based on fundamental concepts of mathematical morphology. The algorithm distinguishes between the “pore bodies” and “pore throats,” and establishes their respective volumes and connectivity. The proposed algorithm also produces a stick-and-ball diagram of the rock pore space. The tests on a pack of equal spheres, for which the results are verifiable, confirm its stability. The impact of image resolution on the algorithm output is investigated on the images of computer-generated pore space.

Suggested Citation

  • Silin, Dmitriy & Patzek, Tad, 2006. "Pore space morphology analysis using maximal inscribed spheres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 336-360.
    • Handle: RePEc:eee:phsmap:v:371:y:2006:i:2:p:336-360
    DOI: 10.1016/j.physa.2006.04.048
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    Cited by:

    1. Lijie Feng & Yuxiang Niu & Zhenfeng Liu & Jinfeng Wang & Ke Zhang, 2019. "Discovering Technology Opportunity by Keyword-Based Patent Analysis: A Hybrid Approach of Morphology Analysis and USIT," Sustainability, MDPI, vol. 12(1), pages 1-35, December.
    2. Sadeghi, Mohammad Amin & Khan, Zohaib Atiq & Agnaou, Mehrez & Hu, Leiming & Litster, Shawn & Kongkanand, Anusorn & Padgett, Elliot & Muller, David A. & Friscic, Tomislav & Gostick, Jeff, 2024. "Predicting PEMFC performance from a volumetric image of catalyst layer structure using pore network modeling," Applied Energy, Elsevier, vol. 353(PA).
    3. Xie, Yetong & Li, Jing & Liu, Huimin & Zhang, Kuihua & Li, Junliang & Li, Chuanhua & Zhu, Rui, 2023. "Study on hydro-mechanical-damage coupling seepage in digital shale cores: A case study of shale in Bohai Bay Basin," Energy, Elsevier, vol. 268(C).
    4. Yoon, Byungun & Park, Inchae & Coh, Byoung-youl, 2014. "Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 287-303.
    5. Kristina Rasmusson & Maria Rasmusson & Alexandru Tatomir & Yvonne Tsang & Auli Niemi, 2021. "Exploring residual CO2 trapping in Heletz sandstone using pore‐network modeling and a realistic pore‐space topology obtained from a micro‐CT scan," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 11(5), pages 907-923, October.
    6. Mandzhieva, Radmila & Subhankulova, Rimma, 2021. "Practical aspects of absolute permeability finding for the lattice Boltzmann method and pore network modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    7. Hai Sun & Lian Duan & Lei Liu & Weipeng Fan & Dongyan Fan & Jun Yao & Lei Zhang & Yongfei Yang & Jianlin Zhao, 2019. "The Influence of Micro-Fractures on the Flow in Tight Oil Reservoirs Based on Pore-Network Models," Energies, MDPI, vol. 12(21), pages 1-17, October.
    8. 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).

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