Fig 1.
Simple stratigraphic column of Mesozoic represents some formations in the Eastern Arabian Peninsula [6].
Fig 2.
Micro- and macro-pores characterization workflow based on experimental and digital methods.
Fig 3.
Table 1.
Porosity, bulk volume, and horizontal permeability equations along with their descriptions.
Table 2.
Measured and processed porosity and permeability of the studied plugs in Arab D limestones.
Table 3.
Numerical equations used to study the rock structure heterogeneity using MICP and FIB-SEM dataset.
Fig 4.
Optical photomicrographs at plain polarized light (PPL) showing the intergranular (between micritized grain) and intragranular (within micritized grain) porosities at different magnifications of (A) 2x, (B) 4x, and (C) 10x.
Fig 5.
(A) SEM image on freshly broken surface sample showing a 3D view. (B) FIB-SEM image showing a 2D representation. Both images represent the micropores inside the micritized grains (within grain microporosity) and macropores between the peloids (Intergranular pores).
Fig 6.
In-house MATLAB Interface for thin section image segmentation.
The results obtained include porosity, the distribution of surface area, and the distribution of aspect ratio of sample 1G.
Fig 7.
(1) Thin section photomicrographs of the studied samples at 1.01μm resolution of (A) sample 1G, (B) sample 2R, (C) sample 3R, (D) sample 5W. (2) The resulting output after segmentation process where the black colors showing the pores and white colors display grains. (3) Segmented pore spaces are presented in three colors of red, green, and blue based on the different pore sizes ranges.
Table 4.
Quantifications of porosity from the TS along with surface area mean and aspect ratio at magnification 10x, for corresponding helium porosity values see Table 2.
Fig 8.
Porosity and pore structure characterization from FIB-SEM images using Otsu’s method as thresholding segmentation technique.
Fig 9.
(1) Original and (2) segmented FIB-SEM images where the black colors show the pores and white colors reveal grains. FIB-SEM images of the studied samples. (A) sample 1G, (B) sample 2R, (C) sample 4M, and (D) sample 5W.
Table 5.
Quantifications of porosity from the FIB-SEM along with surface mean and aspect ratio at scale of 0.01 μm to the grain-dominated samples and 0.005 μm for mud-dominated samples using threshold value of 170 for all samples.
For helium porosity values refer to Table 2.
Fig 10.
CT-numbers plots of (A) photoelectric factors and (B) bulk density on the studied samples.
Fig 11.
2D vertical cross section from 3D CT-scan of sample 3R.
(A) original grey level image, (B) original image illustrated using jet color bar.
Fig 12.
Digital image processing results of the three studied samples of grain-dominated limestones with diameter subset 4 mm using MCT.
(A1-C1) after segmentation, (A2-C2) connected and isolated pores, (A3-C3) connected pores, (A4-C4) isolated pores. The blue color represents connected pores and red color represents isolated pores.
Table 6.
DRP results after MCT-scans segmentation and connectivity analysis.
Fig 13.
Image segmentation for samples: (A) sample 1G, and (B) sample 4M. (A1-B1) original images. (A2-B2): binarized image results, where the black pixels denote pores and white pixels show grains.
Fig 14.
(A) Multifractal dimensions (Dq) associated to the FIB-SEM image of the studied samples along with moments order (q) between −11 and11. (B-C) multifractal spectrum of spatial distribution of different pore extraction images for the studied samples. (B) from FIB-SEM imaging; (C) from MICP analysis.
Table 7.
Estimations of singular exponents and multifractal spectrums values from MICP and FIB-SEM analyses.
Fig 15.
Pore-throat size distribution calculated from the MICP curves for (A) grain-dominated and (B) mud-dominated limestones.