Digital rock analysis is very efficient and accurate for evaluating matrix, porosity, and permeability in unconventional reservoirs, especially shales. It has been recognized as one of the most promising emerging technologies in oil and gas development, providing an alternative method to solve problems that are typically difficult to analyze using traditional laboratory techniques. In this study, high-resolution data are acquired from samples with sandstone, carbonate, and shale lithologies using micro- and nano-computed tomography (CT) scanning and a focused ion beam/scanning electron microscope (FIB/SEM), and the pore throat space is extracted using an imaging segmentation process. The extracted pore throat data are statistically analyzed through a digital rock workflow that develops a skeleton network of pore throat channels, generating a distance map of the pore throat channels and values of pore surface area. These data are then used to statistically evaluate pore size and pore throat size distribution, network connectivity, effective porosity, and permeability. By comparing the statistical data for each lithology, useful differences are noted that can possibly be correlated to pore-system characteristics that affect recovery efficiency. Pore-systems are important because they control both the volume and flow characteristics of hydrocarbon, which are crucial to recovery efficiency. A lithologically distinct statistical evaluation is used to determine the representative elemental volume (REV) as based on the stable pore throat size trends using curve-fitting functions that are uniquely distinct for each lithology. These functions effectively act as a potential fingerprint for each distinctive lithology. Data are presented to determine a specific correlation between parameters for appropriate REV for certain rock types, and differences in conventional and unconventional reservoirs are discussed. Conclusions regarding the reservoir formations and oil/gas volume and flow capabilities are presented.