Name:
Multiscale_RerC_Fuel.pdf
Size:
9.422Mb
Format:
PDF
Description:
Accepted manuscript
Embargo End Date:
2022-12-21
Type
ArticleAuthors
Wang, Yuzhu
Sun, Shuyu

KAUST Department
Computational Transport Phenomena Laboratory (CTPL), Division of Physical Sciences and Engineering (PSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Date
2020-12-21Embargo End Date
2022-12-21Submitted Date
2020-07-13Permanent link to this record
http://hdl.handle.net/10754/666654
Metadata
Show full item recordAbstract
The 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.Citation
Wang, Y., & Sun, S. (2021). Multiscale pore structure characterization based on SEM images. Fuel, 289, 119915. doi:10.1016/j.fuel.2020.119915Publisher
Elsevier BVJournal
FuelAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S0016236120329112ae974a485f413a2113503eed53cd6c53
10.1016/j.fuel.2020.119915