气候变化领域集成服务门户(CCPortal): 3D Carbonate Digital Rock Reconstruction Using Progressive Growing GAN

CCPortal

DOI	10.1029/2021JB021687
	3D Carbonate Digital Rock Reconstruction Using Progressive Growing GAN
	You N.; Li Y.E.; Cheng A.
发表日期	2021
ISSN	21699313
卷号	126 期号:5
英文摘要	The development of digital rock physics relies on the availability of high-quality 3D digital rock images, which can be directly obtained with X-ray micro-Computed Tomography (μCT). However, X-ray μCT is hampered by its high expenses, small sample size (several millimeters in diameter) and low resolution (in micron scale). Although Scanning Electron Microscope (SEM) provides higher resolution on larger rock samples, it only images the 2D rock surface structure. Thus, 3D digital rock reconstruction from 2D cross-section images becomes promising in saving imaging cost for μCT scan and improving image quality by enabling the incorporation of SEM images in 3D digital rock reconstruction. Here, we propose a machine learning method to reconstruct 3D digital rocks from 2D cross-section images taken at large constant intervals along the axial direction of the rock sample. The key idea is to train a Progressive Growing Generative Adversarial Network (PG-GAN) to generate high-quality gray-scale cross-section images, and then reconstruct the 3D digital rock by linearly interpolating the inverted latent vectors corresponding to the sparsely scanned images. We apply our method to reconstructing a large-size high-resolution 3D image of an Estaillades carbonate rock sample. We demonstrate that both the reconstructed image and the extracted pore network are visually indistinguishable from the ground truth. Overall, our method achieves nine times speedup of the imaging process, and greater than 4,500 times compression of the image data for the Estaillades carbonate rock sample. The PG-GAN can enlarge the digital rock repository and enable efficient imaging editing in its linear latent space. © 2021. American Geophysical Union. All Rights Reserved.
语种	英语
来源期刊	Journal of Geophysical Research: Solid Earth
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/187142
作者单位	Department of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore
推荐引用方式 GB/T 7714	You N.,Li Y.E.,Cheng A.. 3D Carbonate Digital Rock Reconstruction Using Progressive Growing GAN[J],2021,126(5).
APA	You N.,Li Y.E.,&Cheng A..(2021).3D Carbonate Digital Rock Reconstruction Using Progressive Growing GAN.Journal of Geophysical Research: Solid Earth,126(5).
MLA	You N.,et al."3D Carbonate Digital Rock Reconstruction Using Progressive Growing GAN".Journal of Geophysical Research: Solid Earth 126.5(2021).