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Deep learning of subsurface flow via theory-guided neural network

Journal of hydrology (Amsterdam), 2020-05, Vol.584, p.124700, Article 124700

2020

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Inverse Modeling for Subsurface Flow Based on Deep Learning Surrogates and Active Learning Strategies

Water resources research, 2023-07, Vol.59 (7), p.n/a

2023

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Deep‐Learning‐Based Inverse Modeling Approaches: A Subsurface Flow Example

Journal of geophysical research. Solid earth, 2021-02, Vol.126 (2), p.n/a

2021

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Surrogate model based iterative ensemble smoother for subsurface flow data assimilation

Advances in water resources, 2017-02, Vol.100, p.96-108

2017

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Tuning Fractures With Dynamic Data

Water resources research, 2018-02, Vol.54 (2), p.680-707

2018

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History matching of facies distribution with the EnKF and level set parameterization

Journal of computational physics, 2010-10, Vol.229 (20), p.8011-8030

2010

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Benchmark problems for subsurface flow uncertainty quantification

Journal of hydrology (Amsterdam), 2015-12, Vol.531, p.168-186

2015

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Identification of a soil water flow equation using a two-step data-driven method

Journal of hydrology (Amsterdam), 2023-07, Vol.622, p.129707, Article 129707

2023

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Editorial: Applications of artificial intelligence in the oil and gas industry

Frontiers in earth science (Lausanne), 2023-03, Vol.11

2023

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Identification of physical processes via combined data-driven and data-assimilation methods

Journal of computational physics, 2019-09, Vol.393, p.337-350

2019

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History matching of facies distribution with varying mean lengths or different principle correlation orientations

Journal of petroleum science & engineering, 2014-12, Vol.124, p.275-292

2014

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Jointly updating the mean size and spatial distribution of facies in reservoir history matching

Computational geosciences, 2015-08, Vol.19 (4), p.727-746

2015

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DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm

Journal of computational physics, 2020-10, Vol.418, p.109584, Article 109584

2020

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

Computer methods in applied mechanics and engineering, 2021-01, Vol.373, p.113492, Article 113492

2021

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Machine learning subsurface flow equations from data

Computational geosciences, 2019-10, Vol.23 (5), p.895-910

2019

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

Computer methods in applied mechanics and engineering, 2021-11, Vol.385, p.114037, Article 114037

2021

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The Dynamic Changes of Brassica napus Seed Microbiota across the Entire Seed Life in the Field

Plants (Basel), 2024-03, Vol.13 (6), p.912

2024

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Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network

Journal of computational physics, 2022-10, Vol.466, p.111419, Article 111419

2022

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Image Classification Algorithm Based on Big Data and Multilabel Learning of Improved Convolutional Neural Network

Wireless communications and mobile computing, 2021, Vol.2021 (1)

2021

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Ensemble Neural Networks (ENN): A gradient-free stochastic method

Neural networks, 2019-02, Vol.110, p.170-185

2019

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Identification of physical processes and unknown parameters of 3D groundwater contaminant problems via theory-guided U-net

Stochastic environmental research and risk assessment, 2024-03, Vol.38 (3), p.869-900

2024

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Deep learning based closed-loop well control optimization of geothermal reservoir with uncertain permeability

Renewable energy, 2023-07, Vol.211, p.379-394

2023

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Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network

Computational geosciences, 2023-12, Vol.27 (6), p.913-938

2023

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Higher density planting benefits mechanical harvesting of rapeseed in the Yangtze River Basin of China

Field crops research, 2018-04, Vol.218, p.97-105

2018

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History matching of statistically anisotropic fields using the Karhunen-Loeve expansion-based global parameterization technique

Computational geosciences, 2014-04, Vol.18 (2), p.265-282

2014

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Deep learning of subsurface flow via theory-guided neural network

Inverse Modeling for Subsurface Flow Based on Deep Learning Surrogates and Active Learning Strategies

Deep‐Learning‐Based Inverse Modeling Approaches: A Subsurface Flow Example

Surrogate model based iterative ensemble smoother for subsurface flow data assimilation

Tuning Fractures With Dynamic Data

History matching of facies distribution with the EnKF and level set parameterization

Benchmark problems for subsurface flow uncertainty quantification

Identification of a soil water flow equation using a two-step data-driven method

Editorial: Applications of artificial intelligence in the oil and gas industry

Identification of physical processes via combined data-driven and data-assimilation methods

History matching of facies distribution with varying mean lengths or different principle correlation orientations

Jointly updating the mean size and spatial distribution of facies in reservoir history matching

DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm

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

Machine learning subsurface flow equations from data

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

The Dynamic Changes of Brassica napus Seed Microbiota across the Entire Seed Life in the Field

Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network

Image Classification Algorithm Based on Big Data and Multilabel Learning of Improved Convolutional Neural Network

Ensemble Neural Networks (ENN): A gradient-free stochastic method

Identification of physical processes and unknown parameters of 3D groundwater contaminant problems via theory-guided U-net

Deep learning based closed-loop well control optimization of geothermal reservoir with uncertain permeability

Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network

Higher density planting benefits mechanical harvesting of rapeseed in the Yangtze River Basin of China

History matching of statistically anisotropic fields using the Karhunen-Loeve expansion-based global parameterization technique

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