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Ying Da Wang
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Year
Deep Learning in Pore Scale Imaging and Modeling
YD Wang, MJ Blunt, RT Armstrong, P Mostaghimi
Earth Science Reviews, 2021
1342021
Enhancing resolution of digital rock images with Super Resolution Convolutional Neural Networks
YD Wang, RT Armstrong, P Mostaghimi
Journal of Petroleum Science and Engineering 182, 2019
1182019
Deep Neural Networks for Improving Physical Accuracy of 2D and 3D Multi-Mineral Segmentation of Rock Micro-CT Images
YD Wang, M Shabaninejad, RT Armstrong, P Mostaghimi
Applied Soft Computing, 2021
99*2021
Boosting Resolution and Recovering Texture of 2D and 3D micro‐CT Images with Deep Learning
YD Wang, RT Armstrong, P Mostaghimi
Water Resources Research, 2020
892020
In-situ hydrogen wettability characterisation for Underground Hydrogen Storage
S Higgs, YD Wang, C Sun, J Ennis-King, SJ Jackson, RT Armstrong, ...
International Journal of Hydrogen Energy, 2022
772022
DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials
A Rabbani, M Babaei, R Shams, Y Da Wang, T Chung
Advances in Water Resources 146, 103787, 2020
692020
ML-LBM: predicting and accelerating steady state flow simulation in porous media with convolutional neural networks
YD Wang, T Chung, RT Armstrong, P Mostaghimi
Transport in Porous Media 138 (1), 49-75, 2021
66*2021
Computations of permeability of large rock images by dual grid domain decomposition
YD Wang, T Chung, RT Armstrong, JE McClure, P Mostaghimi
Advances in water resources 126, 1-14, 2019
622019
Approximating permeability of microcomputed-tomography images using elliptic flow equations
T Chung, YD Wang, RT Armstrong, P Mostaghimi
SPE Journal 24 (03), 1154-1163, 2019
582019
Accelerated computation of relative permeability by coupled morphological and direct multiphase flow simulation
YD Wang, T Chung, RT Armstrong, J McClure, T Ramstad, P Mostaghimi
Journal of Computational Physics 401, 108966, 2020
452020
An innovative application of generative adversarial networks for physically accurate rock images with an unprecedented field of view
Y Niu, YD Wang, P Mostaghimi, P Swietojanski, RT Armstrong
Geophysical Research Letters 47 (23), e2020GL089029, 2020
422020
Flow-based characterization of digital rock images using deep learning
NJ Alqahtani, T Chung, YD Wang, RT Armstrong, P Swietojanski, ...
SPE Journal 26 (04), 1800-1811, 2021
392021
Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning
YD Wang, Q Meyer, K Tang, JE McClure, RT White, ST Kelly, ...
Nature Communications 14 (1), 745, 2023
282023
Voxel agglomeration for accelerated estimation of permeability from micro-CT images
T Chung, Y Da Wang, RT Armstrong, P Mostaghimi
Journal of Petroleum Science and Engineering 184, 106577, 2020
282020
CNN-PFVS: integrating neural network and finite volume models to accelerate flow simulation on pore space images
T Chung, Y Da Wang, RT Armstrong, P Mostaghimi
Transport in Porous Media 135, 25-37, 2020
222020
Super-resolved segmentation of X-ray images of carbonate rocks using deep learning
NJ Alqahtani, Y Niu, YD Wang, T Chung, Z Lanetc, A Zhuravljov, ...
Transport in Porous Media 143 (2), 497-525, 2022
182022
Geometrical-based generative adversarial network to enhance digital rock image quality
Y Niu, YD Wang, P Mostaghimi, JE McClure, J Yin, RT Armstrong
Physical Review Applied 15 (6), 064033, 2021
182021
Generalizable framework of unpaired domain transfer and deep learning for the processing of real-time synchrotron-based x-ray microcomputed tomography images of complex structures
K Tang, Y Da Wang, J McClure, C Chen, P Mostaghimi, RT Armstrong
Physical Review Applied 17 (3), 034048, 2022
162022
Segmentation of x-ray images of rocks using deep learning
I Ar Rushood, N Alqahtani, YD Wang, M Shabaninejad, R Armstrong, ...
SPE Annual Technical Conference and Exhibition?, D041S042R002, 2020
152020
Deep Learning for Full-Feature X-ray Microcomputed Tomography Segmentation of Proton Electron Membrane Fuel Cells
K Tang, Q Meyer, R White, RT Armstrong, P Mostaghimi, YD Wang, S Liu, ...
Computers & Chemical Engineering, 107768, 2022
142022
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