ERL FISH: You Nan (Purdue U.)

Friday, December 02, 2022 at 12:00pm to 1:00pm

Building 54, Room 209
21 AMES ST, Cambridge, MA 02139

"3D Carbonate Digital Rock Reconstruction using Progressive Growing GAN," hosted virtually by MIT Earth Resources Laboratory.

"Digital Rock Physics relies on the availability of high-resolution, large-size 3D digital rock images. In practice, there is always a trade-off between the size and resolution of the acquired images. Moreover, it is time-consuming to acquire high-quality digital rock images using imaging techniques like X-ray micro-Computed Tomography (mCT) and Scanning Electron Microscope (SEM). In this paper, we propose an ML-aided 3D reconstruction method that allows to reduce the sampling rate along the axial direction during image acquisition. 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 to reconstruct the 3D digital rock by linearly interpolating the inverted latent vectors corresponding to the sparsely scanned cross-section images. We apply our method to an Estaillades carbonate rock sample. We observe 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 over 4,500 times compression of the image data for the Estaillades carbonate rock sample. Moreover, the PG-GAN can enlarge the digital rock repository and enable efficient imaging editing in its linear latent space." Dr. Nan You is a Postdoc from the Department of Earth, Atmospheric, and Planetary Sciences at Purdue University. She obtained her B.Eng. in hydrogeology from Nanjing University in 2016 and her Ph.D. in Geophysics from National University of Singapore in 2021. She has been working on ML-based interpretation and integration of different data types (e.g., digital rocks, lab data, and well logs) for comprehensive and efficient rock characterization. She worked with scientists from Halliburton and ExxonMobil to develop real-time automatic ML tools for well-log processing and interpretation. Her paper, "3D carbonate digital rock reconstruction using progressive growing GAN" (You, N., Y. E. Li, and A. Cheng, 2021), was selected in Eos Editors’ Highlight. 

About this series: The Earth Resources Laboratory (ERL) Friday Informal Seminar Hour presents guest speakers on geophysics, seismology, inversion, imaging, ML, and the energy industry. Contact for more information and Zoom password.


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