Inconsistencies are commonplace in identifyingpetrophysical rock classes and geological depositionalfacies in carbonate formations. Different diageneticprocesses may cause the same geological facies toexhibit different petrophysical properties. Theseinconsistencies can be overcome by quantitatively takinginto account spatial distribution of pore network and rockfabric in rock classification and petrophysicalevaluation. Mercury Injection Capillary Pressure(MICP)-based pore typing does take into account thepore structure through pore size distribution. However,such measurements are not commonly available in allwells and depth intervals of interest. Furthermore, welllog-based rock classification techniques do not take intoaccount rock fabric and require the number of rockclasses as an input parameter. There is often uncertaintyin the optimum number of rock classes, which mainlyroots in the differences between petrophysical rockclasses and the geological depositional facies. In thispaper, we introduce a method to (a) evaluate porenetwork connectivity and geometry as rock fabric usingcombined evaluation of pore- and log-scalemeasurements in each rock class, (b) improve rockclassification in carbonate formations by simultaneouslyevaluating conducting porosity, permeability, and rockclasses in the formation, and (c) optimize the number ofrock classes in the formation.
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