Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network

25 April 2020

Papers citing "Efficient Uncertainty Quantification for Dynamic Subsurface Flow with Surrogate by Theory-guided Neural Network"

6 / 6 papers shown

Title
Neural Operator-Based Proxy for Reservoir Simulations Considering Varying Well Settings, Locations, and Permeability Fields Daniel Badawi Eduardo Gildin OOD AI4CE 21 4 0 13 Jul 2024
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 32 18 0 27 Oct 2022
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model Jun Yu Li Dongxiao Zhang Tianhao He Q. Zheng AI4CE 27 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 22 29 0 23 Apr 2022
Deep learning based closed-loop optimization of geothermal reservoir production Nanzhe Wang Haibin Chang Xiangzhao Kong M. Saar Dongxiao Zhang 16 7 0 15 Apr 2022
Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling Nanzhe Wang Haibin Chang Dongxiao Zhang AI4CE 39 49 0 17 Nov 2020