Morphological properties of unconventional reservoir rocks are essential factors determining their fluid flow characteristics and entrapment capability. In particular, shale formations exhibit discernible attributes, including an extensive spectrum of pore sizes spanning from the nano-scale to the micro-scale, although limited pore connectivity results in extremely poor permeability. In this study, Gondwana shale from West Bokaro Region, India, has been analyzed using digital X-ray imaging and numerical simulations of fluid flow to asses the dependency of various properties on the depth of the core samples. A computational approach enables the study of the internal pore network and fluid flow region within the shale sample, unlike the more traditional techniques of measurement of petrophysical parameters by experimental methods. The shale samples are digitized using x-ray computer tomography and binary threshold segmentation. Morphological characteristics are obtained through pore network modelling using the maximal ball algorithm, while the lattice Boltzmann method has been used to simulate fluid flows in the pore spaces. The effects of overburden pressure due to different depths of the sample resulted in reduced pore sizes and lesser connectivity of the pores; for the deeper sample, the porosity distribution is more homogeneous, although the complexity of the pore network is enhanced. Finally, the permeability of the samples is obtained, which indicates a possible role of pore size distribution in the enhanced fluid entrapment capability of the deeper sample.
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