Multiscale Digital Porous Rock Reconstruction Using Template Matching
Abstract
Rocks are heterogeneous multiscale porous media: two rock samples with identical bulk properties can vary widely in microstructure. The advent of digital rock technology and modern 3‐D printing provides new opportunities to replicate rocks. However, the inherent trade‐off between imaging resolution and sample size limits the scales over which microstructure and macrostructure can be identified and related to each other. Here, we develop a multiscale digital rock construction strategy by combining X‐ray computed microtomography and focused‐ion beam (FIB)‐scanning electron microscope (SEM) images, and we apply the technique to a tight sandstone. The computed tomography (CT) scanning images characterize macroscale pore structures, while the FIB‐SEM images capture microscale pore textures. The FIB‐SEM images are then coupled to CT images via a template‐matching algorithm and superposition. Bulk properties, including porosity and pore and throat size distribution, can be recovered with this approach. Permeability prediction with a pore network model for the largest connected pore network are 3 orders and 1 order of magnitude greater than the bulk rock measured value using the CT‐only and the SEM‐CT coupled images, respectively.
Additional Information
© 2019 American Geophysical Union. Issue Online: 02 October 2019; Version of Record online: 19 August 2019; Accepted manuscript online: 30 July 2019; Manuscript accepted: 21 July 2019; Manuscript revised: 12 July 2019; Manuscript received: 24 March 2019. We gratefully acknowledge financial support from the National Science and Technology Major Project of China (2017ZX05013‐001 and 2017ZX05069‐003), the Miller Institute for Basic Research in Science (X. F.), and NSF 1724469 (M. M.); thank China Scholarship Council for funding Wei Lin's visiting study at University of California Berkeley; and are also grateful to Petrochina Company Limited for providing the software "Multi‐scale 3D reconstruction and dynamic simulation system of tight reservoir digital rock" (Registered Copyright No. 2019SR0150745) in this study. The reviewers and editors' comments are highly appreciated. The authors want to thank Senior Engineer Hekun Guo and Dr. Haibo Li from Research Institute of Petroleum Exploration and Development, PetroChina Company Limited, for their technical support in the rate‐controlled mercury intrusion experiment and also would like to especially recognize Juan Wang from China Oilfield Services Limited for the expertise and help in data processing. The data used in this paper are deposited in the Baidu Web Drive and can be downloaded at the website https://pan.baidu.com/s/1lQX00KTvy‐3vcFdxn6Nq6A (code: noeb).Errata
The affiliations of several authors have been corrected since this article was originally published. The affiliation of "A. Gong, G. Chen, H. Li, L. Pei, & S. Li" is the College of Computer and Communication Engineering, China University of Petroleum (East China), Qingdao, P. R. China. W. Lin, X. Li, Z. Yang, S. Xiong, X. Zhao, & X. Wang affiliate to the Research Institute of Petroleum Exploration & Development, PetroChina Company Limited, Beijing, P.R. China, but not the College of Computer and Communication Engineering, China University of Petroleum (East China), Qingdao, P. R. China. The corrected version may be considered the version of record.Attached Files
Published - 2019WR025219.pdf
Supplemental Material - wrcr24124-sup-0001-2019wr025219-si.docx
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Additional details
- Eprint ID
- 106835
- Resolver ID
- CaltechAUTHORS:20201127-170855399
- National Science and Technology Major Project of China
- 2017ZX05013‐001
- National Science and Technology Major Project of China
- 2017ZX05069‐003
- Miller Institute for Basic Research in Science
- NSF
- EAR-1724469
- China Scholarship Council
- Created
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2020-12-02Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field