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A Deep-Learning-Based Geological Parameterization for History Matching
  Complex Models

A Deep-Learning-Based Geological Parameterization for History Matching Complex Models

7 July 2018
Yimin Liu
Wenyue Sun
L. Durlofsky
ArXivPDFHTML

Papers citing "A Deep-Learning-Based Geological Parameterization for History Matching Complex Models"

14 / 14 papers shown
Title
Conditional Deep Generative Models for Belief State Planning
Conditional Deep Generative Models for Belief State Planning
Antoine Bigeard
Anthony Corso
Mykel J. Kochenderfer
AI4CE
24
0
0
16 May 2025
Uncertainty quantification of two-phase flow in porous media via
  coupled-TgNN surrogate model
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model
Jun Yu Li
Dongxiao Zhang
Tianhao He
Q. Zheng
AI4CE
27
6
0
28 May 2022
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization
Valentin Breaz
Richard D. Wilkinson
26
0
0
17 Apr 2022
Deep reinforcement learning for optimal well control in subsurface
  systems with uncertain geology
Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology
Y. Nasir
L. Durlofsky
OffRL
AI4CE
27
17
0
24 Mar 2022
Deep Learning for Simultaneous Inference of Hydraulic and Transport
  Properties
Deep Learning for Simultaneous Inference of Hydraulic and Transport Properties
Zitong Zhou
N. Zabaras
D. Tartakovsky
26
16
0
24 Oct 2021
Applications of physics-informed scientific machine learning in
  subsurface science: A survey
Applications of physics-informed scientific machine learning in subsurface science: A survey
A. Sun
H. Yoon
C. Shih
Zhi Zhong
AI4CE
29
10
0
10 Apr 2021
3D CNN-PCA: A Deep-Learning-Based Parameterization for Complex Geomodels
3D CNN-PCA: A Deep-Learning-Based Parameterization for Complex Geomodels
Yimin Liu
L. Durlofsky
AI4CE
24
60
0
16 Jul 2020
Objective-Sensitive Principal Component Analysis for High-Dimensional
  Inverse Problems
Objective-Sensitive Principal Component Analysis for High-Dimensional Inverse Problems
M. Elizarev
A. Mukhin
A. Khlyupin
21
3
0
02 Jun 2020
Recent Developments Combining Ensemble Smoother and Deep Generative
  Networks for Facies History Matching
Recent Developments Combining Ensemble Smoother and Deep Generative Networks for Facies History Matching
S. A. Canchumuni
J. D. B. Castro
Júlia Potratz
A. Emerick
M. Pacheco
22
47
0
08 May 2020
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series
  Parameterization
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization
Su Jiang
L. Durlofsky
27
18
0
30 Apr 2020
Multiphase flow prediction with deep neural networks
Multiphase flow prediction with deep neural networks
Gege Wen
Meng Tang
S. Benson
24
6
0
21 Oct 2019
A deep-learning-based surrogate model for data assimilation in dynamic
  subsurface flow problems
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems
Meng Tang
Yimin Liu
L. Durlofsky
AI4CE
32
257
0
16 Aug 2019
Integration of adversarial autoencoders with residual dense
  convolutional networks for estimation of non-Gaussian hydraulic
  conductivities
Integration of adversarial autoencoders with residual dense convolutional networks for estimation of non-Gaussian hydraulic conductivities
S. Mo
N. Zabaras
Xiaoqing Shi
Jichun Wu
19
43
0
26 Jun 2019
Towards a Robust Parameterization for Conditioning Facies Models Using
  Deep Variational Autoencoders and Ensemble Smoother
Towards a Robust Parameterization for Conditioning Facies Models Using Deep Variational Autoencoders and Ensemble Smoother
S. A. Canchumuni
A. Emerick
M. Pacheco
OOD
AI4CE
30
109
0
17 Dec 2018
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