Luiz F. Bez, Ricardo Leiderman, André Souza, Rodrigo B. de V. Azeredo, André M. B. Pereira
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The chosen explicit time-integration scheme uses a lumped capacitance formulation and stabilization via hyperbolization, and it is capable of handling arbitrary time-step sizes with controllable error levels. The image-based representation of the pore space is used for a memory-efficient, matrix-free formulation of the time integration using massively parallel processes on a single GPU. In addition, we propose the substitution of a global digital roughness correction factor that depends on the porous space’s geometry for a problem-independent local correction factor, based on nodal neighborhoods. We show that the numerical scheme converges with successive refinements as expected and that our local correction coefficient is capable of estimating the correct <i>S</i>/<i>V</i> parameter of several different classical geometries. We tested our formulation against an image-based Random Walk simulation of four digital rock core samples, achieving good agreement between them. We manage to simulate a giga-voxel image-based model on a personal use GPU (less than 10GB of memory use) in 33 min with our FEM implementation.</p></div>","PeriodicalId":804,"journal":{"name":"Transport in Porous Media","volume":"151 12","pages":"2405 - 2430"},"PeriodicalIF":2.7000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large Scale Voxel-Based FEM Formulation for NMR Relaxation in Porous Media\",\"authors\":\"Luiz F. Bez, Ricardo Leiderman, André Souza, Rodrigo B. de V. Azeredo, André M. B. Pereira\",\"doi\":\"10.1007/s11242-024-02118-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Nuclear magnetic resonance (NMR) techniques are key in the study of porous reservoir rocks. They can provide valuable insight into the pore size distribution of the pore space of a given rock sample due to its dependence on the magnetic fluid/matrix interaction. The pore space is often studied at the μm scale through the use of micro-CT images, which are often composed of hundreds of millions of voxels, posing significant challenges to numerical simulations. In this paper, we present an image-based, fully explicit, and matrix-free finite element implementation for the simulation of NMR relaxation process that is capable of handling such large 3D problems in single GPUs. The chosen explicit time-integration scheme uses a lumped capacitance formulation and stabilization via hyperbolization, and it is capable of handling arbitrary time-step sizes with controllable error levels. The image-based representation of the pore space is used for a memory-efficient, matrix-free formulation of the time integration using massively parallel processes on a single GPU. In addition, we propose the substitution of a global digital roughness correction factor that depends on the porous space’s geometry for a problem-independent local correction factor, based on nodal neighborhoods. We show that the numerical scheme converges with successive refinements as expected and that our local correction coefficient is capable of estimating the correct <i>S</i>/<i>V</i> parameter of several different classical geometries. We tested our formulation against an image-based Random Walk simulation of four digital rock core samples, achieving good agreement between them. We manage to simulate a giga-voxel image-based model on a personal use GPU (less than 10GB of memory use) in 33 min with our FEM implementation.</p></div>\",\"PeriodicalId\":804,\"journal\":{\"name\":\"Transport in Porous Media\",\"volume\":\"151 12\",\"pages\":\"2405 - 2430\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transport in Porous Media\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11242-024-02118-4\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transport in Porous Media","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11242-024-02118-4","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Large Scale Voxel-Based FEM Formulation for NMR Relaxation in Porous Media
Nuclear magnetic resonance (NMR) techniques are key in the study of porous reservoir rocks. They can provide valuable insight into the pore size distribution of the pore space of a given rock sample due to its dependence on the magnetic fluid/matrix interaction. The pore space is often studied at the μm scale through the use of micro-CT images, which are often composed of hundreds of millions of voxels, posing significant challenges to numerical simulations. In this paper, we present an image-based, fully explicit, and matrix-free finite element implementation for the simulation of NMR relaxation process that is capable of handling such large 3D problems in single GPUs. The chosen explicit time-integration scheme uses a lumped capacitance formulation and stabilization via hyperbolization, and it is capable of handling arbitrary time-step sizes with controllable error levels. The image-based representation of the pore space is used for a memory-efficient, matrix-free formulation of the time integration using massively parallel processes on a single GPU. In addition, we propose the substitution of a global digital roughness correction factor that depends on the porous space’s geometry for a problem-independent local correction factor, based on nodal neighborhoods. We show that the numerical scheme converges with successive refinements as expected and that our local correction coefficient is capable of estimating the correct S/V parameter of several different classical geometries. We tested our formulation against an image-based Random Walk simulation of four digital rock core samples, achieving good agreement between them. We manage to simulate a giga-voxel image-based model on a personal use GPU (less than 10GB of memory use) in 33 min with our FEM implementation.
期刊介绍:
-Publishes original research on physical, chemical, and biological aspects of transport in porous media-
Papers on porous media research may originate in various areas of physics, chemistry, biology, natural or materials science, and engineering (chemical, civil, agricultural, petroleum, environmental, electrical, and mechanical engineering)-
Emphasizes theory, (numerical) modelling, laboratory work, and non-routine applications-
Publishes work of a fundamental nature, of interest to a wide readership, that provides novel insight into porous media processes-
Expanded in 2007 from 12 to 15 issues per year.
Transport in Porous Media publishes original research on physical and chemical aspects of transport phenomena in rigid and deformable porous media. These phenomena, occurring in single and multiphase flow in porous domains, can be governed by extensive quantities such as mass of a fluid phase, mass of component of a phase, momentum, or energy. Moreover, porous medium deformations can be induced by the transport phenomena, by chemical and electro-chemical activities such as swelling, or by external loading through forces and displacements. These porous media phenomena may be studied by researchers from various areas of physics, chemistry, biology, natural or materials science, and engineering (chemical, civil, agricultural, petroleum, environmental, electrical, and mechanical engineering).