Show simple item record

dc.contributor.authorWang, Yuzhu
dc.contributor.authorSun, Shuyu
dc.date.accessioned2020-12-27T06:11:52Z
dc.date.available2020-12-27T06:11:52Z
dc.date.issued2020-12-21
dc.date.submitted2020-07-13
dc.identifier.citationWang, Y., & Sun, S. (2021). Multiscale pore structure characterization based on SEM images. Fuel, 289, 119915. doi:10.1016/j.fuel.2020.119915
dc.identifier.issn0016-2361
dc.identifier.doi10.1016/j.fuel.2020.119915
dc.identifier.urihttp://hdl.handle.net/10754/666654
dc.description.abstractThe micropore structure’s permeability contribution to total permeability of the heterogeneous reservoir with multiscale pore structures is critical for reservoir evaluation but still not well understood. This paper proposes a multiscale pore structure characterization method based on high-resolution SEM images to quantitatively analyse the micropore structures’ content and their permeability contributions via six steps. First, the image-based rock typing is implemented to classify a multiscale pore structure into different rock types using the random forest algorithm. Second, the 3D model of the macropore structure and every micropore structure is reconstructed applying the MPS method. Third, the permeability of each reconstructed 3D micropore structure is calculated using LBM, and the corresponding permeability REV of this structure is estimated. Four, an upscaling process is carried out to divide the reconstructed 3D macropore structure into many cells whose length is determined by the maximum permeability REV of the micropore structures. Five, the permeability of every cell of the coarse grid is calculated by LBM except some cells that are randomly selected as micropore structures whose permeability is assigned directly according to their rock types. Finally, the permeability contribution of each micropore structure is evaluated by comparing the permeability calculated before and after assuming the target micropore structure is impermeable. The result shows that the permeability contribution of a micropore structure varies significantly according to its permeability, content, spatial distribution, and the permeability of the macropore structure.
dc.language.isoen
dc.publisherElsevier BV
dc.relation.urlhttps://linkinghub.elsevier.com/retrieve/pii/S0016236120329112
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Fuel. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Fuel, [289, , (2020-12-21)] DOI: 10.1016/j.fuel.2020.119915 . © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMultiscale porous structure
dc.subjectRock typing
dc.subjectMPS
dc.subjectPermeability contribution
dc.titleMultiscale pore structure characterization based on SEM images
dc.typeArticle
dc.contributor.departmentComputational Transport Phenomena Laboratory (CTPL), Division of Physical Sciences and Engineering (PSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalFuel
dc.rights.embargodate2022-12-21
dc.eprint.versionPost-print
dc.identifier.volume289
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
dc.identifier.pages119915
pubs.publication-statusPublished
kaust.personWang, Yuzhu
kaust.personSun, Shuyu
dc.date.accepted2020-11-29
refterms.dateFOA2020-12-27T06:11:52Z


Files in this item

Thumbnail
Name:
Multiscale_RerC_Fuel.pdf
Size:
9.422Mb
Format:
PDF
Description:
Accepted manuscript
Embargo End Date:
2022-12-21

This item appears in the following Collection(s)

Show simple item record