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Multi-energy X-ray CT and data-constrained modeling of shale 3D microstructure

  • Jianli Li

    Jianli Li born in 1991, received her bachelor’s degree in physics at the Lu Liang University, China, in 2015. Currently, she is a PhD candidate in condensed matter physics at the Institute of Theoretical physics, Shanxi University, China, from 2015 to 2021. She works on X-ray CT imaging experiment and material structure characterization.

         , Yu-Shuang Yang , Haipeng Wang EMAIL logo , Lingjie Yu

    Lingjie Yu born in 1982, is a senior geologist in the Wuxi Research Institute of Petroleum Geology, SINOPEC, China. He is currently a PhD student in China University of Petroleum (East China). His main research areas are characterization techniques for unconventional energy reservoir structure and exploration technology for the unconventional energy.

         , Keyu Liu , Jie Ma and Yadong Wei
Published/Copyright: February 21, 2022
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Materials Testing
From the journal Materials Testing Volume 64 Issue 1

Abstract

Three Longmaxi Formation shale samples from different well depths were analyzed for their total organic carbon (TOC) content and mineral phases. Synchrotron-based multi-energy X-ray computed tomography (CT) slices have been acquired for these samples. Deviations of the sample center away from the harmonic trajectory during X-ray CT imaging were corrected to improve the accuracy of CT reconstructed tomographic slices. The three-dimensional (3D) distribution of porosity and mineral in the samples was derived using the data-constrained modeling (DCM) method. The equivalent spherical diameters of connected pore-organics clusters and the connection probabilities were calculated to evaluate the spatial agglomeration and the spatial correlation of pore-organics in the samples. Numerical results showed that the distribution of the connected regions size and the connection probabilities of pore-organics for three samples have similar characteristics. The connection probabilities versus the distance follow exponential law. The connection probability appeared to be positively correlated to the number of pore-organics connected clusters when the distance between the voxels is shorter than 10 μm. Comparing samples from the three well depths, both the numbers of connected regions and connection probabilities of the samples from a deeper well are higher. The approach would be applicable for structural characterization of other similar materials.

Keywords: data-constrained modeling; microstructure; shale; spatial correlation; X-ray CT
Corresponding author: Haipeng Wang, School of Physics & Electronic Engineering, Shanxi University, Taiyuan, Shanxi 030006, China, E-mail:

Funding source: National Basic Research Program of China

Award Identifier / Grant number: 2014CB239004

Funding source: National Nature Science Foundation of China http://dx.doi.org/10.13039/501100001809

Award Identifier / Grant number: 21206087

Funding source: National Nature Science Foundation of China “Petroleum Accumulation Mechanism” Innovative Group Project

Award Identifier / Grant number: 41821002

About the authors

Jianli Li

Jianli Li born in 1991, received her bachelor’s degree in physics at the Lu Liang University, China, in 2015. Currently, she is a PhD candidate in condensed matter physics at the Institute of Theoretical physics, Shanxi University, China, from 2015 to 2021. She works on X-ray CT imaging experiment and material structure characterization.

Lingjie Yu

Lingjie Yu born in 1982, is a senior geologist in the Wuxi Research Institute of Petroleum Geology, SINOPEC, China. He is currently a PhD student in China University of Petroleum (East China). His main research areas are characterization techniques for unconventional energy reservoir structure and exploration technology for the unconventional energy.

Acknowledgment

The authors are grateful to the X-ray CT imaging beam line scientists Tiqiao Xiao, Guohao Du and Yanan Fu from the Shanghai Synchrotron Radiation Facility for their assistance with the experiment.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This study was supported by the National Basic Research Program of China (grant number 2014CB239004), the National Nature Science Foundation of China (grant number 21206087) and the National Nature Science Foundation of China “Petroleum Accumulation Mechanism” Innovative Group Project (grant number 41821002).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Published Online: 2022-02-21
Published in Print: 2022-01-27

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/mt-2021-2030
Keywords for this article
data-constrained modeling; microstructure; shale; spatial correlation; X-ray CT

Articles in the same Issue

  1. Frontmatter
  2. Control of the bainitic structure for a wear-resisting hard-faced rail track
  3. Numerical and experimental formability analysis of aluminum 3105 sandwich panels produced by continuous hot-press forming
  4. Online monitoring of 3D printing of steel via optical emission spectroscopy
  5. Effect of heat treatment on microstructure and properties of modified hypereutectic high chromium cast iron
  6. Characterization of Fe2B layers on ASTM A1011 steel and modeling of boron diffusion
  7. Corrosion behavior of 316 stainless steel, copper, and brazed joint in lithium bromide solution at different temperatures
  8. Effect of austempering treatment on metallurgical structure of Ce inoculated X210Cr12 cold work tool steel
  9. Effects of laser and electron beam welding on the mechanical properties of bake hardening sheets
  10. Analysis of residual stresses and distortions of a titanium alloy ring-stiffened cylindrical shell
  11. Multi-energy X-ray CT and data-constrained modeling of shale 3D microstructure
  12. Forming evolution of titanium grade2 sheets
  13. Effect of Cloisite 15A on the mechanical properties of an abaca-based composite
  14. Comparison of three methods for measuring the bending stiffness of ultrafine metal wires
  15. Surface preparation effects on anodization and corrosion resistance of pure titanium grade 2
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