Permeability prediction for natural porous rocks through feature selection and machine learning
The relationships between macroscopic properties and microstructural characteristics are of
great significance for natural porous rocks, based on which transport properties can be …
great significance for natural porous rocks, based on which transport properties can be …
[HTML][HTML] A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation
Understanding the microstructure–property relationships of porous media is of great
practical significance, based on which macroscopic physical properties can be directly …
practical significance, based on which macroscopic physical properties can be directly …
[HTML][HTML] Predicting permeability via statistical learning on higher-order microstructural information
Quantitative structure–property relationships are crucial for the understanding and prediction
of the physical properties of complex materials. For fluid flow in porous materials …
of the physical properties of complex materials. For fluid flow in porous materials …
A deep learning perspective on predicting permeability in porous media from network modeling to direct simulation
Predicting the petrophysical properties of rock samples using micro-CT images has gained
significant attention recently. However, an accurate and an efficient numerical tool is still …
significant attention recently. However, an accurate and an efficient numerical tool is still …
A New Stochastic Pore-Scale Simulation and Machine Learning Approach to Predicting Permeability and Tortuosity of Heterogeneous Porous Media
OA Ishola - 2023 - search.proquest.com
A new 3D stochastic pore-scale simulation approach was introduced in this study to
investigate how stochastic pore connectivity impacts the permeability and hydraulic …
investigate how stochastic pore connectivity impacts the permeability and hydraulic …
Machine Learning Assisted Prediction of Porosity and Related Properties Using Digital Rock Images
Accurately estimating reservoir rock properties is paramount for modeling the storage and
flow of fluids (hydrocarbon, carbon dioxide, and groundwater) in porous media. However …
flow of fluids (hydrocarbon, carbon dioxide, and groundwater) in porous media. However …
[PDF][PDF] Machine Learning Application for Permeability Estimation of Three-Dimensional Rock Images.
Estimation of permeability in porous media is fundamental to understanding coupled multi-
physics processes critical to various geoscience and environmental applications. Recent …
physics processes critical to various geoscience and environmental applications. Recent …
Improved permeability prediction of porous media by feature selection and machine learning methods comparison
JW Tian, C Qi, K Peng, Y Sun… - Journal of Computing in …, 2022 - ascelibrary.org
Permeability of subsurface porous media is one of the primary factors that affect fluid
transport in porous rock. However, accurate prediction of rock permeability is a challenging …
transport in porous rock. However, accurate prediction of rock permeability is a challenging …
Machine learning modeling of permeability in 3D heterogeneous porous media using a novel stochastic pore-scale simulation approach
Accurate predictions of rock permeability is critical for resource exploration and
environmental management. To improve on existing approaches to permeability prediction …
environmental management. To improve on existing approaches to permeability prediction …
Knowledge extraction via machine learning guides a topology‐based permeability prediction model
The complexity and heterogeneity of pore structure present significant challenges in
accurate permeability estimation. Commonly used empirical formulas neglect its microscopic …
accurate permeability estimation. Commonly used empirical formulas neglect its microscopic …
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