A new method to reconstruct structured mesh model from micro-computed tomography images of porous media and its application

Song, Rui; Li, Jianjun; Cui, Mengmeng

doi:10.1016/j.ijheatmasstransfer.2017.02.053

Cited by 93 publications

(40 citation statements)

References 27 publications

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“…To investigate fluid flow through realistic pore geometry of the porous medium, the 3‐D reconstructed model has to be transformed into an appropriate finite element mesh. Following previous studies (Bird et al, ; Song et al, ; Yan et al, ), we use HyperMesh to transform CT images into a suitable finite element. The work flow of numerical meshing is shown in Figure a.…”

Section: Materials and Methods Core‐scale Pore Structure Reconstructiomentioning

confidence: 99%

Pore‐Scale Reconstruction and Simulation of Non‐Darcy Flow in Synthetic Porous Rocks

et al. 2018

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We image synthetic porous rocks of varied porosity and pore size by micro–computed tomography with pore‐scale finite element modeling representing the pore space for single‐phase fluid flow. The simulations quantify the key features of microscale flow behavior in the synthetic cores. The smaller the permeability, the greater the critical pressure gradient required for the onset of non‐Darcy fluid flows, and the easier the emergence of nonlinear seepage within the tested cores. The relationship between permeability and porosity from different methods shows a power law correlation with pressure. Structural heterogeneity and anisotropy of the pore systems are shown to have a significant impact on transport through the three‐dimensional pore model—exhibiting irregular flow fields. The simulated permeabilities of the tested cores vary by a factor of 2–5 depending on the fluid flow directions. With the increase of flow seepage velocity, the flow regime deviates from Darcy linear relationship and non‐Darcy behavior (inertia) leads to a reduction in the effective permeability of the core. Both experiments and modeling demonstrate that the larger the porosity and permeability, the stronger the non‐linear phenomenon of the seepage within the pore space. A method is proposed to estimate the non‐Darcy coefficient β based on simulation results, which provides a good prediction for all the tested cores. A new equation is established to predict the transition of flow patterns as a function of the apparent permeability K* and Reynolds number Re. The K*‐Re model provides a theoretical approach to dynamically describe the transition from Darcy to Forchheimer flow.

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Section: Materials and Methods Core‐scale Pore Structure Reconstructiomentioning

confidence: 99%

Pore‐Scale Reconstruction and Simulation of Non‐Darcy Flow in Synthetic Porous Rocks

et al. 2018

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“…The standard process of CT scanning is illustrated in Figure . During the scanning, the sample stage is rotated at a specific time, so that the core plug can be scanned by X‐ray from a different direction …”

Section: Methodology and Theoriesmentioning

confidence: 99%

Comparative analysis on pore‐scale permeability prediction on micro‐CT images of rock using numerical and empirical approaches

Song

Wang

Liu

et al. 2019

Energy Science & Engineering

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Varieties of pore‐scale numerical and empirical approaches have been proposed to predict the rock permeability when the pore structure is known, for example, microscopic computerized tomography (micro‐CT) technology. A comparative study on these approaches is conducted in this paper. A reference dataset of nine micro‐CT images of porous rocks is generated and processed including artificial sandpacks, tight sandstone, and carbonate. Multiple numerical and empirical approaches are used to compute the absolute permeability of micro‐CT images including the image voxel‐based solver (VBS), pore network model (PNM), Lattice Boltzmann method (LBM), Kozeny‐Carman (K‐C) equation, and Thomeer relation. Computational accuracy and efficiency of different numerical approaches are investigated. The results indicate that good agreements among numerical solvers are achieved for the sample with a homogeneous structure, while the disagreement increases with an increase in heterogeneity and complexity of pore structure. The LBM and VBS solver both have a relative higher computation accuracy, whereas the PNM solver is less accurate due to simplification on the topological structure. The computation efficiency of the different solver is generally computation resources dependent, and the PNM solver is the fastest, followed by VBS and LBM solver. As expected, empirical relation can over‐estimate permeability by a magnification of 50 or more, particularly for those strong heterogeneous structures reported in this study. Nevertheless, empirical relation is still applicable for artificial rocks.

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“…The reconstruction process of micro pore structure can be mainly divided into the following steps: first, finish the extraction of typical image of pore structure and conduct the image processing, then acquire the profile of pore structure and skeleton, subsequently establish the vector file of pore structure, then lead the vector file into finite element software to obtain the geometric model for calculation, and finally complete the reconstruction of pore structure [14,15]. The generation of mesh can be done in the finite element software, and it can also be conducted in third party software (such as ICEM and other types of professional software for mesh).…”

Section: Reconstruction Of Pore Structure By Conventional Methodmentioning

confidence: 99%

A Pore Scale Flow Simulation of Reconstructed Model Based on the Micro Seepage Experiment

2017

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Researches on microscopic seepage mechanism and fine description of reservoir pore structure play an important role in effective development of low and ultralow permeability reservoir. The typical micro pore structure model was established by two ways of the conventional model reconstruction method and the built-in graphics function method of Comsol5 in this paper. A pore scale flow simulation was conducted on the reconstructed model established by two different ways using creeping flow interface and Brinkman equation interface, respectively. The results showed that the simulation of the two models agreed well in the distribution of velocity, pressure, Reynolds number, and so on. And it verified the feasibility of the direct reconstruction method from graphic file to geometric model, which provided a new way for diversifying the numerical study of micro seepage mechanism.

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A new method to reconstruct structured mesh model from micro-computed tomography images of porous media and its application

Cited by 93 publications

References 27 publications

Pore‐Scale Reconstruction and Simulation of Non‐Darcy Flow in Synthetic Porous Rocks

Pore‐Scale Reconstruction and Simulation of Non‐Darcy Flow in Synthetic Porous Rocks

Comparative analysis on pore‐scale permeability prediction on micro‐CT images of rock using numerical and empirical approaches

A Pore Scale Flow Simulation of Reconstructed Model Based on the Micro Seepage Experiment

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