Abstract
This study automates a type-curve technique for estimating the rock pore-geometric factor (A.) from capillary pressure measurements. The pore-geometric factor is determined by matching the actual rock capillary pressure versus wetting-phase saturation (Pc-Sw) profile with that obtained from the Brooks and Corey model (1966./. Irrigation Drainage Proc. Am. Soc. Civ. Eng. 61-88). The pore-geometric factor values are validated by comparing the actual measured rock permeability to the permeability values estimated using the Wyllie and Gardner model (1958 World Oil (April issue) 210-28). Petrophysical data for both carbonate and sandstone rocks, along with the pore-geometric factor derived from the type-curve matching, are used in a discriminant analysis for the purpose of developing a model for rock typing. The petrophysical parameters include rock porosity (φ), irreducible water saturation (Swi), permeability (κ), the threshold capillary-entry-pressure (pd), a pore-shape factor (β), and a flow-impedance parameter (n) which is a properly that reflects the How impedance caused by the irreducible wetting-phase saturation. The results of the discriminant analysis indicate that live of the parameters (φ, κ, Pd, λ and n) are sufficient for classifying rocks according to two broad lithology classes: sandstones and carbonates. The analysis reveals the existence of a significant discriminant function that is mostly sensitive to the pore-geometric factor values (λ). A discriminant-analysis classification model that honours both static and dynamic petrophysical rock properties is, therefore, introduced. When tested on two distinct data sets, the discriminant-analysis model was able to predict the correct lithofacies for approximately 95% of the tested samples. A comprehensive database of the experimentally collected petrophysical properties of 215 carbonate and sandstone rocks is provided with this study.
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Al-Omair, O., & Garrouch, A. A. (2010). Classifying rock lithofacies using petrophysical data. Journal of Geophysics and Engineering, 7(3), 302–320. https://doi.org/10.1088/1742-2132/7/3/009
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