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The paper presents a workflow for fast pore-scale simulation of single-phase flow in tight reservoirs typically characterized by low, multiscale porosity. Multiscale porosity implies that the computational domain contains porous voxels…

X-ray micro-computed tomography (X-ray microCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major…

This work introduces a novel application for predicting the macroscopic intrinsic permeability tensor in deformable porous media, using a limited set of micro-CT images of real microgeometries. The primary goal is to develop an efficient,…

Fluid Dynamics · Physics 2025-01-14 Yousef Heider , Fadi Aldakheel , Wolfgang Ehlers

Porous materials are widely used in different applications, in particular they are used to create various filters. Their quality depends on parameters that characterize the internal structure such as porosity, permeability and so on.…

Computer Vision and Pattern Recognition · Computer Science 2019-10-18 V. Kokhan , M. Grigoriev , A. Buzmakov , V. Uvarov , A. Ingacheva , E. Shvets , M. Chukalina

Fluid flow through intricate confining geometries often exhibits complex behaviors, certainly in porous materials, e.g. in groundwater flows or the operation of filtration devices and porous catalysts. However, it has remained extremely…

Direct pore scale simulations of two-fluid flow on digital rock images provide a promising tool to understand the role of surface wetting phenomena on flow and transport in geologic reservoirs. We present computational protocols that mimic…

Geophysics · Physics 2020-07-27 James E. McClure , Zhe Li , Mark Berrill , Thomas Ramstad

Quantitative image analysis often depends on accurate classification of pixels through a segmentation process. However, imaging artifacts such as the partial volume effect and sensor noise complicate the classification process. These…

Computer Vision and Pattern Recognition · Computer Science 2018-08-01 Brendan A. West , Taylor S. Hodgdon , Matthew D. Parno , Arnold J. Song

Permeability and heat transport through building materials ultimately dictates their insulatory performance over a buildings service lifetime. Experiments combining XCT with numerical modelling are an accepted method of studying pore scale…

Materials Science · Physics 2024-05-31 Hannah P. Menke , Katherine M. Hood , Kamaljit Singh , Gabriela M. Medero , Julien Maes

This study presents a novel workflow for constructing hybrid macropore-Darcy models from micro-CT images of microporous rocks. In our approach, macropore networks are extracted using established methods, while the microporosity is…

This study refutes the premise that the distribution of flow speeds in complex porous media can be described by a simple function such as a normal or exponential variation. In many complex porous media, including those relevant for…

Fluid Dynamics · Physics 2018-08-21 Branko Bijeljic , Ali Q. Raeini , Qingyang Lin , Martin J. Blunt

In recent years, convolutional neural networks (CNNs) have experienced an increasing interest in their ability to perform a fast approximation of effective hydrodynamic parameters in porous media research and applications. This paper…

Machine Learning · Computer Science 2022-04-14 Stephan Gärttner , Faruk O. Alpak , Andreas Meier , Nadja Ray , Florian Frank

Field-of-view and resolution trade-offs in X-Ray micro-computed tomography (micro-CT) imaging limit the characterization, analysis and model development of multi-scale porous systems. To this end, we developed an applied methodology…

Studying porous rock materials with X-Ray Computed Tomography (XRCT) has been established as a standard procedure for the non-destructive visualization of flow and transport in opaque porous media. Despite the recent advances in the field…

Machine Learning · Computer Science 2022-05-19 Dongwon Lee , Nikolaos Karadimitriou , Matthias Ruf , Holger Steeb

Pore-network modeling is a widely used predictive tool for pore-scale studies in various applications that deal with multiphase flow in porous media. Despite recent improvements to enable pore-network modeling on simplified pore geometry…

Computational Physics · Physics 2020-04-06 Amir H. Kohanpur , Albert J. Valocchi

This study presents a comprehensive workflow for investigating particulate materials through combined 360{\deg} electron tomography (ET), nano-computed X-ray tomography (nanoCT), and micro-computed X-ray tomography (microCT), alongside a…

This study investigates the use of High-Performance Computing (HPC) to simulate flow and transport in ultra-large micro-CT images of porous materials using Computational Fluid Dynamics (CFD). Two distinct rock samples, representative of two…

Fluid Dynamics · Physics 2025-12-10 J. Maes , Gavin J. Pringle , Hannah P. Menke

Recent advances in (scanning) transmission electron microscopy have enabled routine generation of large volumes of high-veracity structural data on 2D and 3D materials, naturally offering the challenge of using these as starting inputs for…

Data Analysis, Statistics and Probability · Physics 2022-11-08 Ayana Ghosh , Maxim Ziatdinov , Ondrej Dyck , Bobby Sumpter , Sergei V. Kalinin

In situ synchrotron X-ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts - like ring and cupping effects - and limited training data. We present a…

We present an image processing algorithm developed for quantitative analysis of directional solidification of metal alloys in thin cells using X-ray imaging. Our methodology allows to identify the fluid volume, fluid channels and cavities,…

Materials Science · Physics 2023-08-02 Mihails Birjukovs , Natalia Shevchenko , Sven Eckert

Fast multi-phase processes in methane hydrate-bearing samples are challenging for micro-CT quantitative study because of complex tomographic data analysis involving time-consuming segmentation procedures. This is due to the sample…

Geophysics · Physics 2022-09-12 Mikhail I. Fokin , Viktor V. Nikitin , Anton A. Duchkov
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