资源环境科技发展态势分析平台

Carbonate rocks store half of the world's proven oil reserves. Genesis and postdepositional diagenetic processes define the porous network topology and the matrix permeability. This study compiles a database of porosity, specific surface, mercury porosimetry, and permeability values extracted from published sources and complements the database through a focused experimental study. Specific surface and porosity combine to estimate the pore size (D-sur). Permeability versus D-sur. data duster along a single trend with a slope of 2 in a log-log scale, which is in agreement with the Kozeny-Carman model. Discordant data points correspond to samples with dual porosity or broad pore-size distributions with long tails, where flow channels along larger interconnected pores. Indeed, the detailed analysis of all the porosimetry data in the database shows that permeability correlates best with the pore size D80, that is, the 80th percentile in pore-size distributions. Once again, the best fit is a power function in terms of (D80)(2), analogous to Kozeny-Carman. The prediction uncertainty using D80 is one order of magnitude and has the same degree of uncertainty as more complex models and analyses. This observation suggests an irreducible uncertainty of one order of magnitude in permeability estimation from index properties such as porosity, mercury porosimetry, and specific surface probably resulting from specimen preparation effects, inherent physical differences in permeation versus invasion, and difficulties in data interpretation. These estimates of permeability are most valuable when specimens are limited to small sizes, such as cuttings.