A new approach to predict carbonate lithology from well logs: A case study of the Kometan formation in northern Iraq

Abstract

Understanding the spatial variation in lithology is crucial for characterizing reservoirs, as it governs the distribution of petrophysical characteristics. This study focuses on predicting the lithology of carbonate rocks (limestone, argillaceous limestone, marly limestone, and marl) within the Kometan Formation, Khabbaz Oil Field, Northern Iraq, using well logs. Precise lithology prediction was achieved by applying multivariate regression method on neutron, sonic, and density logs. Gamma-ray and elemental concentrations from bulk-rock X-ray fluorescence spectroscopy were employed to identify clay minerals, paleoenvironments, and quantify the shale content. The results indicate that the Kometan Formation predominantly comprises limestone, marl, marly limestone, and argillaceous limestone in the middle section. The middle part exhibits a higher shale content compared to the lower and upper parts. A statistically significant correlation (R2 = 0.83–0.85) between described and predicted lithology was established. The model with a higher coefficient of determination (0.85) was tested for further predictions in other wells in the Kirkuk Oil Field. This research can be valuable for lithological and petrophysical characterization of carbonate reservoirs and electrofacies analysis, particularly in situations where core data is unavailable.

Keywords

• Multivariate regression
• Lithology prediction
• Gamma-ray log
• Porosity logs