Analysis of reconstructed multisource and multiscale 3-D digital rocks based on the cycle-consistent generative adversarial network method

Author:

Yan Weichao123,Chi Peng4ORCID,Golsanami Naser56,Sun Jianmeng4,Xing Huilin123,Li Sanzhong12,Dong Huaimin7

Affiliation:

1. Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Lab of Submarine Geosciences and Prospecting Techniques, MOE and College of Marine Geosciences, Ocean University of China , Qingdao 266100 , China

2. Deep-Sea Multidisciplinary Research Center, National Laboratory for Marine Science and Technology (Qingdao) , Qingdao 266237 , China

3. International Center for Submarine Geosciences and Geoengineering Computing (iGeoComp), Ocean University of China , Qingdao 266100 , China

4. School of Geosciences, China University of Petroleum (East China) , Qingdao 266580 , China

5. State Key Laboratory of Mining Disaster Prevention and Control, Shandong University of Science and Technology , Qingdao 266590 , China

6. College of Energy and Mining Engineering, Shandong University of Science and Technology , Qingdao 266590 , China

7. School of Geological Engineering and Geomatics, Chang'an University , Xi'an 710064 , China

Abstract

SUMMARY Digital rock physics (DRP) is important for characterizing the pore characteristics and petrophysical parameters of rocks from a microscopic perspective. Among the digital rock reconstruction methods, the most widely used is the computer tomography (CT) scan method. However, the pore structure of rocks has multiscale features, and CT scan images with a single resolution cannot completely describe the pore structure characteristics of rocks. In this paper, we analysed reconstructed multisource and multiscale 3-D digital rocks based on the cycle-consistent generative adversarial network (CycleGAN) method. This method fully integrates the advantages of the large field of view of low-resolution images and the high-precision features of high-resolution images. To investigate the performance of the method, two sequences of CT scan images of a sandstone (sample A) and a carbonate rock (sample B) collected from oilfields were studied. Moreover, due to the high resolution of scanning electron microscope (SEM) images, we also constructed 3-D digital rocks with different resolutions of the Berea sandstone based on the combination of CT scan images and SEM images. Finally, the statistical properties and absolute permeabilities were calculated to evaluate the accuracies of reconstructed multisource and multiscale 3-D digital rocks. The results show that the reconstructed multiscale digital rocks based on the CycleGAN method have good accuracy in terms of statistical properties and petrophysical properties. Considering the computational cost and computational accuracy, for high- and low-resolution CT scan images and CT scan images with SEM images as training image data sources, we suggest that the resolution of the reconstructed multiscale digital cores is 4–8 times and 4–16 times higher than that of the low-resolution CT scan images, respectively. The findings of our research will be helpful in gaining insight into the petrophysical properties of heterogeneous rocks.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Natural Science Foundation of Shaanxi Province

Publisher

Oxford University Press (OUP)

Subject

Geochemistry and Petrology,Geophysics

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