IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i3p680-d488983.html
   My bibliography  Save this article

Does Rheology of Bingham Fluid Influence Upscaling of Flow through Tight Porous Media?

Author

Listed:
  • Tong Liu

    (Department of Engineering Mechanics and CNMM, Tsinghua University, Beijing 100084, China)

  • Shiming Zhang

    (Exploration and Development Research Institute, Shengli Oil Company, Sinopec, Dongying 257015, China)

  • Moran Wang

    (Department of Engineering Mechanics and CNMM, Tsinghua University, Beijing 100084, China)

Abstract

Non-Newtonian fluids may cause nonlinear seepage even for a single-phase flow. Through digital rock technologies, the upscaling of this non-Darcy flow can be studied; however, the requirements for scanning resolution and sample size need to be clarified very carefully. This work focuses on Bingham fluid flow in tight porous media by a pore-scale simulation on CT-scanned microstructures of tight sandstones. A bi-viscous model is used to depict the Bingham fluid. The results show that when the Bingham fluid flows through a rock sample, the flowrate increases at a parabolic rate when the pressure gradient is small and then increases linearly with the pressure gradient. As a result, an effective permeability and a start-up pressure gradient can be used to characterize this flow behavior. By conducting flow simulations at varying sample sizes, we obtain the representative element volume (REV) for effective permeability and start-up pressure gradient. It is found that the REV size for the effective permeability is almost the same as that for the absolute permeability of Newtonian fluid. The interesting result is that the REV size for the start-up pressure gradient is much smaller than that for the effective permeability. The results imply that the sample size, which is large enough to reach the REV size for Newtonian fluids, can be used to investigate the Bingham fluids flow through porous media as well.

Suggested Citation

  • Tong Liu & Shiming Zhang & Moran Wang, 2021. "Does Rheology of Bingham Fluid Influence Upscaling of Flow through Tight Porous Media?," Energies, MDPI, vol. 14(3), pages 1-15, January.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:3:p:680-:d:488983
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/3/680/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/3/680/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sheppard, Adrian P. & Sok, Robert M. & Averdunk, Holger, 2004. "Techniques for image enhancement and segmentation of tomographic images of porous materials," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 145-151.
    2. Tong Liu & Xu Jin & Moran Wang, 2018. "Critical Resolution and Sample Size of Digital Rock Analysis for Unconventional Reservoirs," Energies, MDPI, vol. 11(7), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shuangmei Zou & Peixing Xu & Congjiao Xie & Xuan Deng & Haodong Tang, 2022. "Characterization of Two-Phase Flow from Pore-Scale Imaging Using Fractal Geometry under Water-Wet and Mixed-Wet Conditions," Energies, MDPI, vol. 15(6), pages 1-17, March.
    2. Jones, A.C. & Sheppard, A.P. & Sok, R.M. & Arns, C.H. & Limaye, A. & Averdunk, H. & Brandwood, A. & Sakellariou, A. & Senden, T.J. & Milthorpe, B.K. & Knackstedt, M.A., 2004. "Three-dimensional analysis of cortical bone structure using X-ray micro-computed tomography," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 125-130.
    3. Turner, M.L. & Knüfing, L. & Arns, C.H. & Sakellariou, A. & Senden, T.J. & Sheppard, A.P. & Sok, R.M. & Limaye, A. & Pinczewski, W.V. & Knackstedt, M.A., 2004. "Three-dimensional imaging of multiphase flow in porous media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 166-172.
    4. Sakellariou, A. & Sawkins, T.J. & Senden, T.J. & Limaye, A., 2004. "X-ray tomography for mesoscale physics applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 152-158.
    5. Aste, T. & Saadatfar, M. & Sakellariou, A. & Senden, T.J., 2004. "Investigating the geometrical structure of disordered sphere packings," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 16-23.
    6. Ma, Tinghuai & Li, Lu & Ji, Sai & Wang, Xin & Tian, Yuan & Al-Dhelaan, Abdullah & Al-Rodhaan, Mznah, 2014. "Optimized Laplacian image sharpening algorithm based on graphic processing unit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 400-410.
    7. Hanwen Yu & Jiaren Ye & Qiang Cao & Yiming Liu & Wei Zhang, 2023. "Study on the Tight Gas Accumulation Process and Model in the Transition Zone at the Margin of the Basin: A Case Study on the Permian Lower Shihezi Formation, Duguijiahan Block, Ordos Basin, Northern C," Energies, MDPI, vol. 16(3), pages 1-30, February.
    8. Tong Liu & Xu Jin & Moran Wang, 2018. "Critical Resolution and Sample Size of Digital Rock Analysis for Unconventional Reservoirs," Energies, MDPI, vol. 11(7), pages 1-15, July.
    9. Mandzhieva, Radmila & Subhankulova, Rimma, 2021. "Practical aspects of absolute permeability finding for the lattice Boltzmann method and pore network modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    10. Salina Borello, Eloisa & Peter, Costanzo & Panini, Filippo & Viberti, Dario, 2022. "Application of A∗ algorithm for microstructure and transport properties characterization from 3D rock images," Energy, Elsevier, vol. 239(PC).
    11. Romain Guibert & Marfa Nazarova & Marco Voltolini & Thibaud Beretta & Gerald Debenest & Patrice Creux, 2022. "Influence of Standard Image Processing of 3D X-ray Microscopy on Morphology, Topology and Effective Properties," Energies, MDPI, vol. 15(20), pages 1-14, October.
    12. Saadatfar, M. & Knackstedt, M.A. & Arns, C.H. & Sakellariou, A. & Senden, T.J. & Sheppard, A.P. & Sok, R.M. & Steininger, H. & Schrof, W., 2004. "Polymeric foam properties derived from 3D images," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 131-136.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:3:p:680-:d:488983. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.