Computational upscaling of Drucker-Prager plasticity from micro-CT images of synthetic porous rock

被引:12
|
作者
Liu, Jie [1 ,2 ]
Sarout, Joel [3 ]
Zhang, Minchao [1 ]
Dautriat, Jeremie [3 ]
Veveakis, Emmanouil [3 ,4 ]
Regenauer-Lieb, Klaus [4 ]
机构
[1] Sun Yat Sen Univ, Sch Earth Sci & Engn, Guangzhou 510275, Guangdong, Peoples R China
[2] Guangdong Prov Key Lab Mineral Resources & Geol P, Guangzhou 510275, Guangdong, Peoples R China
[3] CSIRO Energy, Perth, WA, Australia
[4] Univ New South Wales, Sch Petr Engn, Sydney, NSW 2052, Australia
基金
澳大利亚研究理事会; 中国国家自然科学基金;
关键词
Microstructure; Plasticity; diffusion and creep; Numerical modelling; TRANSPORT-PROPERTIES; ELASTIC PROPERTIES; MICROTOMOGRAPHY; SANDSTONE;
D O I
10.1093/gji/ggx409
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Quantifying rock physical properties is essential for the mining and petroleum industry. Microtomography provides a new way to quantify the relationship between the microstructure and the mechanical and transport properties of a rock. Studies reporting the use microtomographic images to derive permeability and elastic moduli of rocks are common; only rare studies were devoted to yield and failure parameters using this technique. In this study, we simulate the macroscale plastic properties of a synthetic sandstone sample made of calcite-cemented quartz grains using the microscale information obtained from microtomography. The computations rely on the concept of representative volume elements (RVEs). The mechanical RVE is determined using the upper and lower bounds of finite-element computations for elasticity. We present computational upscaling methods from microphysical processes to extract the plasticity parameters of the RVE and compare results to experimental data. The yield stress, cohesion and internal friction angle of the matrix (solid part) of the rock were obtained with reasonable accuracy. Computations of plasticity of a series of models of different volume-sizes showed almost overlapping stress-strain curves, suggesting that the mechanical RVE determined by elastic computations is also valid for plastic yielding. Furthermore, a series of models were created by self-similarly inflating/deflating the porous models, that is keeping a similar structure while achieving different porosity values. The analysis of these models showed that yield stress, cohesion and internal friction angle linearly decrease with increasing porosity in the porosity range between 8 and 28 per cent. The internal friction angle decreases the most significantly, while cohesion remains stable.
引用
收藏
页码:151 / 163
页数:13
相关论文
共 50 条
  • [1] Multiphase-field modelling of crack propagation in geological materials and porous media with Drucker-Prager plasticity
    Spaeth, Michael
    Herrmann, Christoph
    Prajapati, Nishant
    Schneider, Daniel
    Schwab, Felix
    Selzer, Michael
    Nestler, Britta
    [J]. COMPUTATIONAL GEOSCIENCES, 2021, 25 (01) : 325 - 343
  • [2] Multiphase-field modelling of crack propagation in geological materials and porous media with Drucker-Prager plasticity
    Michael Späth
    Christoph Herrmann
    Nishant Prajapati
    Daniel Schneider
    Felix Schwab
    Michael Selzer
    Britta Nestler
    [J]. Computational Geosciences, 2021, 25 : 325 - 343
  • [3] Direct simulations of two-phase flow on micro-CT images of porous media and upscaling of pore-scale forces
    Raeini, Ali Q.
    Blunt, Martin J.
    Bijeljic, Branko
    [J]. ADVANCES IN WATER RESOURCES, 2014, 74 : 116 - 126
  • [4] Deep learning for lithological classification of carbonate rock micro-CT images
    dos Anjos, Carlos E. M.
    Avila, Manuel R. V.
    Vasconcelos, Adna G. P.
    Neta, Aurea M. Pereira
    Medeiros, Lizianne C.
    Evsukoff, Alexandre G.
    Surmas, Rodrigo
    Landau, Luiz
    [J]. COMPUTATIONAL GEOSCIENCES, 2021, 25 (03) : 971 - 983
  • [5] Deep learning for lithological classification of carbonate rock micro-CT images
    Carlos E. M. dos Anjos
    Manuel R. V. Avila
    Adna G. P. Vasconcelos
    Aurea M. Pereira Neta
    Lizianne C. Medeiros
    Alexandre G. Evsukoff
    Rodrigo Surmas
    Luiz Landau
    [J]. Computational Geosciences, 2021, 25 : 971 - 983
  • [6] Generation of Synthetic Images of Trabecular Bone Based on Micro-CT Scans
    Grande-Barreto, Jonas
    Polanco-Castro, Eduardo
    Peregrina-Barreto, Hayde
    Rosas-Mialma, Eduardo
    Puig-Mar, Carmina
    [J]. INFORMATION, 2023, 14 (07)
  • [7] Rock properties from micro-CT images: Digital rock transforms for resolution, pore volume, and field of view
    Saxena, Nishank
    Hows, Amie
    Hofmann, Ronny
    Alpak, Faruk O.
    Dietderich, Jesse
    Appel, Matthias
    Freeman, Justin
    De Jong, Hilko
    [J]. ADVANCES IN WATER RESOURCES, 2019, 134
  • [8] Thermal-mechanical modelling on cumulative freeze-thaw deformation of porous rock in elastoplastic state based on Drucker-Prager criterion considering dilatancy
    Lv, Zhitao
    Wu, Mingchao
    Wang, Zhaohu
    Zeng, Xiangtai
    [J]. INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, 2024, 180
  • [9] On Representative Elementary Volumes of Grayscale Micro-CT Images of Porous Media
    Singh, Ankita
    Regenauer-Lieb, Klaus
    Walsh, Stuart D. C.
    Armstrong, Ryan T.
    van Griethuysen, Joost J. M.
    Mostaghimi, Peyman
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (15)
  • [10] Deep Learning for Porous Media Classification Based on Micro-CT Images
    Charytanowicz, Malgorzata
    Kowalski, Piotr A.
    Lukasik, Szymon
    Kulczycki, Piotr
    Czachor, Henryk
    [J]. 2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022,