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

Deep learning of subsurface flow via theory-guided neural network

(2020) Nanzhe Wang et al.   JOURNAL OF HYDROLOGY

On the multiscale characterization of effective hydraulic conductivity in random heterogeneous media: A historical survey and some new perspectives

(2020) Iván Colecchio 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

A self-adaptive deep learning algorithm for accelerating multi-component flash calculation

(2020) Tao Zhang 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

Simulator-free solution of high-dimensional stochastic elliptic partial differential equations using deep neural networks

(2019) Sharmila Karumuri et al.   JOURNAL OF COMPUTATIONAL PHYSICS

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

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

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

(2018) Rohit K. Tripathy 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

Constrained probabilistic collocation method for uncertainty quantification of geophysical models

(2015) Qinzhuo Liao et al.   COMPUTATIONAL GEOSCIENCES

Reservoir Description with Integrated Multiwell Data Using Two-Dimensional Wavelets

(2013) Abeeb A. Awotunde et al.   Mathematical Geosciences

Stochastic representation and dimension reduction for non-Gaussian random fields: review and reflection

(2013) Heng Li et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Prediction under Uncertainty on a Mature Field

(2012) M. Feraille et al.   Oil & Gas Science and Technology-Revue d IFP Energies nouvelles

A Comparative Study of the Probabilistic-Collocation and Experimental-Design Methods for Petroleum-Reservoir Uncertainty Quantification

(2011) Heng Li et al.   SPE JOURNAL

Monte Carlo simulation of permeability fields and reservoir performance predictions with SVD parameterization in RML compared with EnKF

(2010) Reza Tavakoli et al.   COMPUTATIONAL GEOSCIENCES

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Compressed History Matching: Exploiting Transform-Domain Sparsity for Regularization of Nonlinear Dynamic Data Integration Problems

(2009) Behnam Jafarpour et al.   Mathematical Geosciences