Application of pore network modeling in deep bed filtration analysis

Particle invasion in porous media is an important phenomenon that could lead to formation damage during different operations, such as waterflooding, workover, and drilling. In this paper, a 3D pore network model coupled with a particle tracking method was developed to investigate particle retention...

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Main Authors: Shabani, A., Zivar, D., Jahangiri, H.R., Shahrabadi, A.
Format: Article
Published: Springer Nature 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100756776&doi=10.1007%2fs42452-020-03356-z&partnerID=40&md5=9c3c2dade24c2376a3f66f176b5134b8
http://eprints.utp.edu.my/30040/
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spelling my.utp.eprints.300402022-03-25T03:22:00Z Application of pore network modeling in deep bed filtration analysis Shabani, A. Zivar, D. Jahangiri, H.R. Shahrabadi, A. Particle invasion in porous media is an important phenomenon that could lead to formation damage during different operations, such as waterflooding, workover, and drilling. In this paper, a 3D pore network model coupled with a particle tracking method was developed to investigate particle retention and permeability reduction of a pore network system. The proposed model considers the effect of hydraulic drag, gravity, and friction forces. Three mechanisms, including surface deposition, straining, and bridging, have been considered in the development of the proposed pore network model. The results of the proposed model show good agreement with experimental data. A sharp permeability reduction is observed in the early time of the injection, which indicates the blockage of the small radius throats by particles, as well as unstable fluid flow due to the distribution of the particles. Moreover, the number of throats with a small radius and different contributing mechanisms cause the discontinuous decrease of the porous media permeability. The proposed pore network modeling demonstrates that a small section of the pore network can reproduce the results of the experiment, and a big pore network that is too time and cost consuming is not required. © 2020, Springer Nature Switzerland AG. Springer Nature 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100756776&doi=10.1007%2fs42452-020-03356-z&partnerID=40&md5=9c3c2dade24c2376a3f66f176b5134b8 Shabani, A. and Zivar, D. and Jahangiri, H.R. and Shahrabadi, A. (2020) Application of pore network modeling in deep bed filtration analysis. SN Applied Sciences, 2 (9). http://eprints.utp.edu.my/30040/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Particle invasion in porous media is an important phenomenon that could lead to formation damage during different operations, such as waterflooding, workover, and drilling. In this paper, a 3D pore network model coupled with a particle tracking method was developed to investigate particle retention and permeability reduction of a pore network system. The proposed model considers the effect of hydraulic drag, gravity, and friction forces. Three mechanisms, including surface deposition, straining, and bridging, have been considered in the development of the proposed pore network model. The results of the proposed model show good agreement with experimental data. A sharp permeability reduction is observed in the early time of the injection, which indicates the blockage of the small radius throats by particles, as well as unstable fluid flow due to the distribution of the particles. Moreover, the number of throats with a small radius and different contributing mechanisms cause the discontinuous decrease of the porous media permeability. The proposed pore network modeling demonstrates that a small section of the pore network can reproduce the results of the experiment, and a big pore network that is too time and cost consuming is not required. © 2020, Springer Nature Switzerland AG.
format Article
author Shabani, A.
Zivar, D.
Jahangiri, H.R.
Shahrabadi, A.
spellingShingle Shabani, A.
Zivar, D.
Jahangiri, H.R.
Shahrabadi, A.
Application of pore network modeling in deep bed filtration analysis
author_facet Shabani, A.
Zivar, D.
Jahangiri, H.R.
Shahrabadi, A.
author_sort Shabani, A.
title Application of pore network modeling in deep bed filtration analysis
title_short Application of pore network modeling in deep bed filtration analysis
title_full Application of pore network modeling in deep bed filtration analysis
title_fullStr Application of pore network modeling in deep bed filtration analysis
title_full_unstemmed Application of pore network modeling in deep bed filtration analysis
title_sort application of pore network modeling in deep bed filtration analysis
publisher Springer Nature
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100756776&doi=10.1007%2fs42452-020-03356-z&partnerID=40&md5=9c3c2dade24c2376a3f66f176b5134b8
http://eprints.utp.edu.my/30040/
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