U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow

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-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow

(2021) Meng Tang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Pore-scale modelling and sensitivity analyses of hydrogen-brine multiphase flow in geological porous media

(2021) Leila Hashemi et al.   Scientific Reports

CCSNet: A deep learning modeling suite for CO2 storage

(2021) Gege Wen et al.   ADVANCES IN WATER RESOURCES

Simulating fluid flow in complex porous materials by integrating the governing equations with deep-layered machines

(2021) Serveh Kamrava et al.   npj Computational Materials

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media

(2021) Kun Wang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Machine Learning in Geo- and Environmental Sciences: From Small to Large Scale

(2020) Pejman Tahmasebi et al.   ADVANCES IN WATER RESOURCES

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

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

SciANN: A Keras/TensorFlow wrapper for scientific computations and physics-informed deep learning using artificial neural networks

(2020) Ehsan Haghighat et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Towards a predictor for CO2 plume migration using deep neural networks

(2020) Gege Wen et al.   International Journal of Greenhouse Gas Control

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

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

Predicting CO 2 Plume Migration in Heterogeneous Formations Using Conditional Deep Convolutional Generative Adversarial Network

(2019) Zhi Zhong et al.   WATER RESOURCES RESEARCH

CO2 plume migration and dissolution in layered reservoirs

(2019) Gege Wen et al.   International Journal of Greenhouse Gas Control

Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification

(2018) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

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

Persistent questions of heterogeneity, uncertainty, and scale in subsurface flow and transport

(2015) Peter K. Kitanidis   WATER RESOURCES RESEARCH

Influence of capillary-pressure models on CO2 solubility trapping

(2013) Boxiao Li et al.   ADVANCES IN WATER RESOURCES

Capillary pressure and heterogeneity for the CO2/water system in sandstone rocks at reservoir conditions

(2011) Ronny Pini et al.   ADVANCES IN WATER RESOURCES

The impact of heterogeneity on the distribution of CO2: Numerical simulation of CO2 storage at Ketzin

(2010) U. Lengler et al.   International Journal of Greenhouse Gas Control

Investigation of CO2 Plume Behavior for a Large-Scale Pilot Test of Geologic Carbon Storage in a Saline Formation

(2009) Christine Doughty   TRANSPORT IN POROUS MEDIA