Theory-guided Auto-Encoder for surrogate construction and inverse modeling

Deep residual U-net convolution neural networks with autoregressive strategy for fluid flow predictions in large-scale geosystems

(2021) Zhihao Jiang et al.   ADVANCES IN WATER RESOURCES

Deep learning of subsurface flow via theory-guided neural network

(2020) Nanzhe Wang et al.   JOURNAL OF HYDROLOGY

Physics-informed semantic inpainting: Application to geostatistical modeling

(2020) Qiang Zheng et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems

(2020) Meng Tang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep-learning-based surrogate model for reservoir simulation with time-varying well controls

(2020) Zhaoyang Larry Jin et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Efficient uncertainty quantification for dynamic subsurface flow with surrogate by Theory-guided Neural Network

(2020) Nanzhe Wang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Deep autoregressive neural networks for high‐dimensional inverse problems in groundwater contaminant source identification

(2019) Shaoxing Mo et al.   WATER RESOURCES RESEARCH

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

(2019) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data

(2019) Luning Sun et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

(2018) Liang Liang et al.   Journal of the Royal Society Interface

Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media

(2018) Shaoxing Mo et al.   WATER RESOURCES RESEARCH

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

An Adaptive Ensemble Smoother With Multiple Data Assimilation for Assisted History Matching

(2016) Duc H. Le et al.   SPE JOURNAL

Levenberg–Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification

(2013) Yan Chen et al.   COMPUTATIONAL GEOSCIENCES