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2004.13560
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Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network
25 April 2020
Nanzhe Wang
Haibin Chang
Dongxiao Zhang
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Papers citing
"Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network"
4 / 4 papers shown
Title
Neural Operator-Based Proxy for Reservoir Simulations Considering Varying Well Settings, Locations, and Permeability Fields
Daniel Badawi
Eduardo Gildin
OOD
AI4CE
11
3
0
13 Jul 2024
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model
Jun Yu Li
Dongxiao Zhang
Tianhao He
Q. Zheng
AI4CE
17
6
0
28 May 2022
Use of Multifidelity Training Data and Transfer Learning for Efficient Construction of Subsurface Flow Surrogate Models
Su Jiang
L. Durlofsky
AI4CE
11
29
0
23 Apr 2022
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling
Nanzhe Wang
Haibin Chang
Dongxiao Zhang
AI4CE
15
48
0
17 Nov 2020
1