Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program
Three-dimensional (3D) microstructure reconstruction is a key approach to exploring the relationship between pore characteristics and physical properties. Viewing the training image as a prior model, multiple-point statistics (MPS) focus on reproducing spatial patterns in the simulation grid. Howeve...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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GeoScienceWorld
2024-01-01
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| Series: | Lithosphere |
| Online Access: | https://pubs.geoscienceworld.org/gsa/lithosphere/article-pdf/2024/1/1/6171660/lithosphere_2023_233.pdf |
| _version_ | 1827370529593491456 |
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| author | Chen Zuo Chen Guo Shi Dong Longhai Yang Haoyue Zhang |
| author_facet | Chen Zuo Chen Guo Shi Dong Longhai Yang Haoyue Zhang |
| author_sort | Chen Zuo |
| collection | DOAJ |
| description | Three-dimensional (3D) microstructure reconstruction is a key approach to exploring the relationship between pore characteristics and physical properties. Viewing the training image as a prior model, multiple-point statistics (MPS) focus on reproducing spatial patterns in the simulation grid. However, it is challenging to efficiently generate 3D nonstationary models with varying microstructures. In this work, we propose column-oriented simulation (ColSIM) to achieve the stochastic reconstruction of 3D porous media. A heterogeneous system is understood as a spatially evolving process that consists of frequent transitions of small magnitude and abrupt changes of large magnitude. First, a training image selection step is suggested to find representative microstructures. Our program applies modified Hausdorff distance, t-distributed stochastic neighboring embedding, and spectral clustering to organize two-dimensional (2D) candidate images. The medoid of each group is applied to guide the following programs. Second, we introduce column-oriented searching into MPS. To save simulation time, a subset of conditioning points is checked to find desired instances. Our program suggests an early stopping strategy to address complex microstructures. Third, a contrastive loss term is designed to create 3D models from 2D slice. To automatically calibrate the volume fraction and simplify parameter specification, the computer consistently monitors the difference between the present model and the target. The performance of ColSIM is examined by 3D multiphase material modeling and 3D heterogeneous shale simulation. To achieve quantitative evaluation, we compute various statistical functions and physical descriptors on simulated realizations. The proposed ColSIM exhibits competitive performance in terms of calculation efficiency, microstructure reproduction, and spatial uncertainty. |
| first_indexed | 2024-03-08T10:16:47Z |
| format | Article |
| id | doaj.art-74ce9c20c7874878a30de914dcace808 |
| institution | Directory Open Access Journal |
| issn | 1941-8264 1947-4253 |
| language | English |
| last_indexed | 2024-03-08T10:16:47Z |
| publishDate | 2024-01-01 |
| publisher | GeoScienceWorld |
| record_format | Article |
| series | Lithosphere |
| spelling | doaj.art-74ce9c20c7874878a30de914dcace8082024-01-28T14:52:25ZengGeoScienceWorldLithosphere1941-82641947-42532024-01-012024112210.2113/2024/lithosphere_2023_233Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics ProgramChen Zuo0https://orcid.org/0000-0002-0115-1674Chen Guo1Shi Dong2Longhai Yang3Haoyue Zhang4Department of Big Data Management and Applications, Chang'an University, Xi'an 710064, ChinaSchool of Information Engineering, Chang'an University, Xi'an 710064, ChinaDepartment of Big Data Management and Applications, Chang'an University, Xi'an 710064, ChinaSchool of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi'an 710064, ChinaSchool of Information Engineering, Chang'an University, Xi'an 710064, ChinaThree-dimensional (3D) microstructure reconstruction is a key approach to exploring the relationship between pore characteristics and physical properties. Viewing the training image as a prior model, multiple-point statistics (MPS) focus on reproducing spatial patterns in the simulation grid. However, it is challenging to efficiently generate 3D nonstationary models with varying microstructures. In this work, we propose column-oriented simulation (ColSIM) to achieve the stochastic reconstruction of 3D porous media. A heterogeneous system is understood as a spatially evolving process that consists of frequent transitions of small magnitude and abrupt changes of large magnitude. First, a training image selection step is suggested to find representative microstructures. Our program applies modified Hausdorff distance, t-distributed stochastic neighboring embedding, and spectral clustering to organize two-dimensional (2D) candidate images. The medoid of each group is applied to guide the following programs. Second, we introduce column-oriented searching into MPS. To save simulation time, a subset of conditioning points is checked to find desired instances. Our program suggests an early stopping strategy to address complex microstructures. Third, a contrastive loss term is designed to create 3D models from 2D slice. To automatically calibrate the volume fraction and simplify parameter specification, the computer consistently monitors the difference between the present model and the target. The performance of ColSIM is examined by 3D multiphase material modeling and 3D heterogeneous shale simulation. To achieve quantitative evaluation, we compute various statistical functions and physical descriptors on simulated realizations. The proposed ColSIM exhibits competitive performance in terms of calculation efficiency, microstructure reproduction, and spatial uncertainty.https://pubs.geoscienceworld.org/gsa/lithosphere/article-pdf/2024/1/1/6171660/lithosphere_2023_233.pdf |
| spellingShingle | Chen Zuo Chen Guo Shi Dong Longhai Yang Haoyue Zhang Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program Lithosphere |
| title | Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program |
| title_full | Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program |
| title_fullStr | Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program |
| title_full_unstemmed | Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program |
| title_short | Stochastic Reconstruction of 3D Heterogeneous Microstructure Using a Column-Oriented Multiple-Point Statistics Program |
| title_sort | stochastic reconstruction of 3d heterogeneous microstructure using a column oriented multiple point statistics program |
| url | https://pubs.geoscienceworld.org/gsa/lithosphere/article-pdf/2024/1/1/6171660/lithosphere_2023_233.pdf |
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