Characterization of Subsurface Hydrogeological Structures With Convolutional Conditional Neural Processes on Limited Training Data-Reference-Cited by-同舟云学术

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Characterization of Subsurface Hydrogeological Structures With Convolutional Conditional Neural Processes on Limited Training Data

Published:2022-12 Issue:12 Volume:58 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Cui Zhesi¹²^ORCID,Chen Qiyu¹²³^ORCID,Liu Gang¹²³^ORCID

Affiliation:

1. School of Computer Science China University of Geosciences Wuhan China

2. Hubei Key Laboratory of Intelligent Geo‐Information Processing China University of Geosciences Wuhan China

3. State Key Laboratory of Biogeology and Environmental Geology China University of Geosciences Wuhan China

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022WR033161

Reference68 articles.

1. An Introduction to Stochastic Processes with Applications to Biology

2. Conditional Simulation with Patterns

3. Downscaling in remote sensing

4. Enduring effect of permeability texture for enhancing accuracy and reducing uncertainty of reservoir fluid flow through porous media

5. Generative adversarial network as a stochastic subsurface model reconstruction

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