Sliced Wasserstein Distance-Guided Three-Dimensional Porous Media Reconstruction Based on Cycle-Consistent Adversarial Network and Few-Shot Learning
Author:
Funder
National Natural Science Foundation of China
State Key Laboratory of Water Resources and Hydropower Engineering Science
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11242-024-02099-4.pdf
Reference78 articles.
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3. Bauer, M., Kostler, H., Rude, U.: lbmpy: Automatic code generation for efficient parallel lattice Boltzmann methods. J. Comput. Sci. 49, 101269 (2021). https://doi.org/10.1016/j.jocs.2020.101269
4. Berrone, S., Hyman, J.D., Pieraccini, S.: Multilevel Monte Carlo predictions of first passage times in three-dimensional discrete fracture networks: a graph-based approach. Water Resour. Res. 56(6), e2019WR026493 (2020). https://doi.org/10.1029/2019WR026493
5. Blunt, M.J., Jackson, M.D., Piri, M., Valvatne, P.H.: Detailed physics, predictive capabilities and macroscopic consequences for pore-network models of multiphase flow. Adv. Water Resour. 25(8–12), 1069–1089 (2002). https://doi.org/10.1016/S0309-1708(02)00049-0
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