Testing and evaluation of 2D/3D digital image analysis methods and inclusion theory for microporosity and S-wave prediction in carbonates

Three digital image analysis (DIA) methods are proposed to evaluate the geometric properties of the pore system in 2D/3D and identify the macro- and mesopores: 1) optical microscopy of thin sections computed by Fiji-ImageJ software, 2) μCT data volume decomposition using 2D slices and Fiji-ImageJ, and 3) application of GEODICT, 2015) software and PoreShape GeoLab routines to compute the 3D pores. Microporosity is characterized using assumptions based on the difference between helium gas and the image porosity and the classification system by Anselmetti et al. and rock physics modeling of the differential effective medium theory is applied to estimate the micropore aspect ratio via Vp, supplying a calibrated method to predict Vs for similar rocks. According to the results, the 2D processing methods (#1 and #2) are more realistic and theoretically consistent for estimating 2D DIA parameters. The approximation of the detected 3D pores to 2D in method #3 results in poor representativeness of the pore texture, limiting the potential usefulness of the μCT data, although the same resolution is inherent to the μCT data volume and is applied in methods #2 and #3. The use of μCT data from 2D slices (method #2) was evaluated as the best method for computing the 2D DIA parameters, and the optical thin sections used in method #1 were limited by differences in the resolution and the low representativeness of the micrograph quantity in correlating the texture complexities. This work generates a valuable outcrop dataset and original discussions of DIA at different image scales for input modeling to match ultrasonic and elastic properties with the lithological characteristics of Oman samples.