Velocity deviation-based pore type classification in an Iranian carbonate gas reservoir using multiscale integrated data

A study has been conducted to classify pore types in a carbonate gas reservoir located in the Dalan/Kangan formations of Iran. The researchers used a multi-scale integrated data approach, incorporating velocity deviation log (VDL) analysis, traditional well logs, Nuclear Magnetic Resonance (NMR) information, and seismic inversion.

The petrographic examination of thin sections provided the initial categorization of pore types within the reservoir, which included moldic, intergranular, intercrystalline, matrix-supported, and smaller amounts of intragranular, vuggy, and fracture types. Moldic porosity, especially in oolitic and bioclastic settings, is the most common but shows varying connectivity due to diagenetic alterations.

This initial analysis set the criteria for assessing the outcomes of later geophysical techniques. VDL was initially calculated by employing standard petrophysical logs and subsequently improved by integrating total porosity from NMR measurements. The spatial distribution of VDL was then employed as a critical input for post-stack seismic inversion, which enabled the prediction of pore types throughout the reservoir.

The results from all methods confirmed the primary pore types across the investigated intervals, demonstrating a high degree of agreement with the thin section findings. Both VDLs, derived from conventional and NMR data, support the prevalence of matrix-supported and moldic porosity, thereby increasing the confidence in the integrated interpretation.

However, there are some discrepancies observed in some intervals where the NMR-derived VDL profile hints at the existence of a compliant pore system/fracture indicator, which was not detected in the petrographic analysis. This difference is believed to be caused by the NMR tool's sensitivity to bound and free fluid distributions, which could potentially imitate fracture signatures in zones with increased microporosity or subtle structural heterogeneities.

This study enhances the reliability of pore type classification in intricate carbonate systems, offering a robust framework for reservoir characterization and modeling. In conclusion, the research emphasizes the importance of integrating advanced petrophysical measurements with seismic interpretation to create more precise subsurface models, which can aid in making informed decisions for reservoir development in Iranian carbonate gas fields.

The authors acknowledge the National Iranian Oil Company (NIOC) for providing the data and their support in carrying out this research. They also express gratitude to the Chemical and Petroleum Engineering Department at Sharif University of Technology in Tehran, Iran, and the Earth Sciences Department at the University of Tabriz in Tabriz, Iran.

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