Microbial carbonates have complex pore networks formed by their biological growth framework, which later may be modified by diagenetic alteration. A proper evaluation of the porous media characteristics and their evolution is essential to better characterize microbial carbonate reservoirs. However, conventional methods of fundamental rock characteristic description are insufficient to elucidate the heterogeneity of pore networks and textural shifts. X-ray computed tomography allows a better evaluation of these fundamental characteristics, which, when integrated with stratigraphic analysis, enhances the understanding of the volume and connectivity of pore networks in different microbial textures. A three-dimensional evaluation of a Holocene microbialite from Brazil provides insights about how the primary pore network is related to the textural changes in microbialite successions, which, in ancient deposits, may be reduced or enhanced by diagenesis. Conventional methods such as petrography, carbon and oxygen stable isotope analysis, and laboratory measurements for porosity and permeability were integrated with computed tomography images and three-dimensional rendering to provide a high-resolution history of the evolution of porosity and permeability within this microbialite. The pore network differences are related to microbial textural evolution driven by environmental changes. The depositional textures control petrophysical properties based on fundamental rock characteristics such as structure size, structure packing, and framework fabric. Those fundamental characteristics influence the pore volume and number of pore throats. Large structures, open packing, and chaotic framework fabric result in a better connected pore network, whereas small structures, tight packing, and organized fabric result in less connected pore networks. Comparative pore geometry analysis of the Upper Jurassic Smackover Formation thrombolites shows that their depositional textures also had high primary porosity values. If the microbial textures and petrophysical properties are environmentally controlled, their prediction in the subsurface is made possible by refined depositional models.