Advanced Applied Geology

Advanced Applied Geology

Comparison of Petrophysical and Statistical Approaches in Rock Typing: Evaluation of Jenks, Winland, and Flow Zone Indicator Methods in the Kangan Formation, Persian Gulf

Authors
School of Geology, College of Science, University of Tehran, Tehran, Iran
Abstract
Heterogeneity in carbonate reservoirs is one of the main challenges in predicting flow behavior and evaluating reservoir quality. The Kangan Formation in the central Persian Gulf represents a typical example of such complexity. The Jenks Natural Breaks algorithm has been widely used in various sciences as for identifying patterns in datasets. In this study, the Jenks method was applied both independently and in combination with common petrophysical indicators, including the Winland and the Flow Zone Indicator (FZI), to a dataset of 483 carbonate core samples in order to evaluate its performance in defining optimal rock type boundaries. Initially, Jenks was used to classify permeability values alone, and then applied to the combined parameter of porosity and permeability. The algorithm was also employed to determine major transition boundaries within the Winland and Flow Zone Indicator frameworks. In the Winland method, the highest coefficient of determination between porosity and permeability was observed in the “Good” class (R² = 0.79). In the Flow Zone Indicator method, strong correlations occurred in the “Mega-tight” (R² = 0.81) and “Intermediate” (R² = 0.68) classes. The Jenks method, when applied as a single-variable classifier, produced weak correlations (maximum R² = 0.13), but its performance improved moderately (R² = 0.57) when using a combined logarithmic parameter (log k / φ). The results indicate that petrophysical index–based methods such as Winland and Flow Zone Indicator provide more consistent rock typing, whereas the Jenks method can be used as a complementary tool for data analysis alongside petrophysical methods.
Keywords
Subjects

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