LIMESTONE TEXTURES AND THEIR CONTROLS ON PORE SIZE DISTRIBUTION
Detailed petrographic work was done through thin sections and SEM analysis. Depositional compositions and pore structures of these samples were quantified by using an in-house developed image analysis software and point counting techniques. In addition, Mercury Injection Capillary Pressure (MICP) data were also used to find the links between pore throat distribution and sedimentary textures. Subsequently, statistics of pore size and pore throat size were integrated with quantified sedimentary textures data to clarify the characteristics of pore size distribution within each rock types.This study demonstrates that petrographic textures exert a major control on the pore structure and size distribution of a limestone reservoir found in the Middle East. In general, the reservoir rocks are composed of various shallow marine limestones including grainstones, packstones, wackestone, mudstones and microbial bindstones. Based on their petrographic textures, the reservoir rocks can be divided into four rock types, each of which shows unique characteristics in its pore structure and pore size distribution. Pore types are dominated by intergranular pores in grain-dominated rock types and intercrystalline pores in mud-dominated rock types. The image analysis results show that microporosity (< ~8 µm in diameter) make up more than 40% of total porosity for all samples and the percentage of microporosity decreases along with increasing in grain contents. SEM analysis also confirms that intercrystalline micropores in micritic matrix are a dominant component of total porosity in mud-rich samples. The existence of micropores complexes the relationship between porosity and permeability of limestones. And also, the microporosity is considered to be the major culprit for the low resistivity pays found in these limestone reservoirs. The links between petrographic textures and pore size distribution revealed by this study suggest that the occurrence of the low resistivity pays in carbonate reservoirs can be predicted by detailed rock type mapping.