A review of proxy modeling highlighting applications for reservoir engineering
Numerical models can be used for many purposes in oil and gas engineering, such as
production optimization and forecasting, uncertainty analysis, history matching, and risk …
production optimization and forecasting, uncertainty analysis, history matching, and risk …
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems
A deep-learning-based surrogate model is developed and applied for predicting dynamic
subsurface flow in channelized geological models. The surrogate model is based on deep …
subsurface flow in channelized geological models. The surrogate model is based on deep …
A review on optimization algorithms and surrogate models for reservoir automatic history matching
Y Zhao, R Luo, L Li, R Zhang, D Zhang, T Zhang… - Geoenergy Science and …, 2024 - Elsevier
Reservoir history matching represents a crucial stage in the reservoir development process
and purposes to match model predictions with various observed field data, including …
and purposes to match model predictions with various observed field data, including …
Learning large-scale subsurface simulations with a hybrid graph network simulator
Subsurface simulations use computational models to predict the flow of fluids (eg, oil, water,
gas) through porous media. These simulations are pivotal in industrial applications such as …
gas) through porous media. These simulations are pivotal in industrial applications such as …
Well trajectory optimization under geological uncertainties assisted by a new deep learning technique
R Yousefzadeh, M Ahmadi - SPE Journal, 2024 - onepetro.org
The large number of geological realizations and well trajectory parameters make field
development optimization under geological uncertainty a time-consuming task. A novel …
development optimization under geological uncertainty a time-consuming task. A novel …
[HTML][HTML] Conditioning of deep-learning surrogate models to image data with application to reservoir characterization
Imaging-type monitoring techniques are used in monitoring dynamic processes in many
domains, including medicine, engineering, and geophysics. This paper aims to propose an …
domains, including medicine, engineering, and geophysics. This paper aims to propose an …
Predicting CO2-EOR and storage in low-permeability reservoirs with deep learning-based surrogate flow models
Addressing the greenhouse effect, enhancing carbon reduction and utilization has become
globally imperative. China has ambitious goals to carbon peak by 2030 and achieve carbon …
globally imperative. China has ambitious goals to carbon peak by 2030 and achieve carbon …
Model‐Reduced Adjoint‐Based Inversion Using Deep‐Learning: Example of Geological Carbon Sequestration Modeling
As an extension of our previous research on deep‐learning‐based adjoint‐state approach
(Xiao, Deng, & Wang, 2021, https://doi. org/10.1029/2020wr027400), we present a two‐level …
(Xiao, Deng, & Wang, 2021, https://doi. org/10.1029/2020wr027400), we present a two‐level …
Surrogate-assisted inversion for large-scale history matching: Comparative study between projection-based reduced-order modeling and deep neural network
History matching can play a key role in improving geological characterization and reducing
the uncertainty of reservoir model predictions. Application of reservoir history matching is …
the uncertainty of reservoir model predictions. Application of reservoir history matching is …
A novel deep learning-based automatic search workflow for CO2 sequestration surrogate flow models
Numerical simulation can significantly enhance subsurface resource utilisation's efficiency
and economic benefits by multiphase flow in heterogeneous porous media. However …
and economic benefits by multiphase flow in heterogeneous porous media. However …