Nanzhe Wang

发表

Deep learning based closed-loop optimization of geothermal reservoir production

Dongxiao Zhang, M. Saar, Xiangzhao Kong, 2022, ArXiv.

Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method

Yuntian Chen, Dongxiao Zhang, Junsheng Zeng, 2020, J. Comput. Phys..

GANSim-surrogate: An integrated framework for conditional geomodelling and uncertainty analysis

Dongxiao Zhang, T. Mukerji, Suihong Song, 2022 .

Efficient well placement optimization based on theory-guided convolutional neural network

Nanzhe Wang, Haibin Chang, Liang Xue, 2022, Journal of Petroleum Science and Engineering.

Deep Learning of Subsurface Flow via Theory-guided Neural Network

Dongxiao Zhang, Heng Li, Nanzhe Wang, 2019, Journal of Hydrology.

Weak Form Theory-guided Neural Network (TgNN-wf) for Deep Learning of Subsurface Single and Two-phase Flow pdf

Rui Xu, Dongxiao Zhang, Nanzhe Wang, 2020, J. Comput. Phys..

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

Haibin Chang, Dongxiao Zhang, Nanzhe Wang, 2020, Computer Methods in Applied Mechanics and Engineering.

Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method pdf

Yuntian Chen, Junsheng Zeng, Nanzhe Wang, 2020, J. Comput. Phys..

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

Dongxiao Zhang, Nanzhe Wang, Haibin Chang, 2020, Journal of Geophysical Research: Solid Earth.

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

Dongxiao Zhang, Nanzhe Wang, Haibin Chang, 2023, Renewable Energy.

Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data pdf

Hao Xu, Dongxiao Zhang, Nanzhe Wang, 2020, J. Comput. Phys..

GANSim-surrogate: An integrated framework for stochastic conditional geomodelling

Dongxiao Zhang, T. Mukerji, Suihong Song, 2023, Journal of Hydrology.

Uncertainty quantification and inverse modeling for subsurface flow in 3D heterogeneous formations using a theory-guided convolutional encoder-decoder network pdf

Dongxiao Zhang, Rui Xu, Nanzhe Wang, 2021, Journal of Hydrology.

Theory-guided full convolutional neural network: An efficient surrogate model for inverse problems in subsurface contaminant transport

Dongxiao Zhang, Tianhao He, Nanzhe Wang, 2021, Advances in Water Resources.

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

Haibin Chang, Dongxiao Zhang, Nanzhe Wang, 2021, J. Comput. Phys..

Solution of diffusivity equations with local sources/sinks and surrogate modeling using weak form Theory-guided Neural Network

Dongxiao Zhang, Rui Xu, Nanzhe Wang, 2021, Advances in Water Resources.

Theory-guided Auto-Encoder for Surrogate Construction and Inverse Modeling pdf

Haibin Chang, Dongxiao Zhang, Nanzhe Wang, 2020, ArXiv.

A Lagrangian dual-based theory-guided deep neural network pdf

Dongxiao Zhang, Nanzhe Wang, Miao Rong, 2020, Complex & Intelligent Systems.

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

Dongxiao Zhang, Nanzhe Wang, Haibin Chang, 2023, Water Resources Research.

Physics-Informed Convolutional Decoder (PICD): A novel approach for direct inversion of heterogeneous subsurface flow

Nanzhe Wang, Xiang-Zhao Kong, Dongxiao Zhang, 2024, 2401.06905.