Digital petrophysics investigates the properties of rocks from images, especially core computed tomography (CT scan). The purpose of these investigations is to develop new methods for petrophysical evaluation of porous materials. In this article, textural parameters have been calculated from computed tomography images of the cores in Permian Dalan Formation in the central Persian Gulf. We tried to find more evidence that industrial CT scan images are useful in identifying the geological and petrophysical characteristics of hydrocarbon reservoirs. For this purpose, the textural parameters of the image, including contrast, correlation, homogeneity, energy and entropy were calculated and analyzed and a gray level co-occurrence matrix has been created. These parameters were compared with geological and petrophysical data obtained from laboratory measurements and thin section studies. Analysis of the thin sections under the microscope led to the identification of 12 microfacies. They range from mudstone to wackestone, packstone and grainstone. Some samples have been completely dolomitized and recognition of their primary microfacies is not possible. This group called crystalline carbonate. Results showed that various features in CT scan images can be differentiated using the arrangement of pixels, the gray intensity of each pixel and the relationship of each pixel to its neighboring pixels. Increasing porosity and permeability reduces the image heterogeneity. This is also the case for uniformly distributed pore types, including moldic and intercrystalline. Textural parameters were also compared with microfacies and diagenetic processes. Results indicate that they can increase heterogeneity with decreasing reservoir quality and vice versa. Finally, using numerical values of image textural parameters, three petrophysical classes were defined in the studied reservoir. As a result, various parts of the reservoir can be identified using CT scan images of the cores.