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DRP-317 Parker Notebook Report

Notebook: 28_mwe_drp317_parker_raw_porosity_perm

Sources

  • Dataset: Neumann, R., ANDREETA, M., Lucas-Oliveira, E. (2020, October 7). 11 Sandstones: raw, filtered and segmented data [Dataset]. Digital Porous Media Portal. https://www.doi.org/10.17612/f4h1-w124
  • Experimental reference paper: Neumann, R. F., Barsi-Andreeta, M., Lucas-Oliveira, E., Barbalho, H., Trevizan, W. A., Bonagamba, T. J., & Steiner, M. B. (2021). High accuracy capillary network representation in digital rock reveals permeability scaling functions. Scientific Reports, 11, 11370. https://doi.org/10.1038/s41598-021-90090-0

Current Setup

  • Raw volume: Parker_2d25um_binary.raw
  • ROI size: (300, 300, 300) voxels
  • Selected ROI origin: (700, 350, 0)
  • ROI porosity: 13.68%
  • Extraction backends: porespy, prego, native_maximal_ball
  • Conductance model: generic_poiseuille
  • Viscosity model: tabulated water viscosity from thermo, 298.15 K
  • Boundary pressures: pout = 5.0 MPa, pin = pout + 10 kPa/m * L

Key Results

Quantity Value
Experimental porosity [%] 14.77
Full-image porosity [%] 13.65
ROI porosity [%] 13.68
Experimental permeability [mD] 10.0
Backend Network phi [%] Kx [mD] Ky [mD] Kz [mD] RMS K [mD] Rel. K error [%] Np Nt
PoreSpy snow2 12.90 20.51 18.17 22.40 20.43 104.32 3454 5647
PREGO 12.57 42.06 40.96 52.90 45.62 356.24 2022 4147
Native maximal-ball 12.57 7.99 7.76 10.37 8.79 -12.14 1975 3133

Parker directional permeability

Network Statistics Snapshot

Backend Mean coordination Dead-end pore fraction
PoreSpy snow2 3.27 0.290
PREGO 4.10 0.116
Native maximal-ball 3.17 0.270

Interpretation

For Parker, the closest aggregate permeability in this rerun is from Native maximal-ball with a relative permeability error of -12.14%. The spread between the largest and smallest backend aggregate permeability is about 5.19x, which makes extraction sensitivity a material part of this sample's validation result.

This is a pore-network comparison against a laboratory-scale experimental reference. The numbers depend on the selected ROI, segmentation convention, boundary labeling, network reduction, and conductance closure; they should not be read as a direct voxel-scale flow simulation.