Quantification of fracture porosity and reservoir heterogeneity in carbonates: An integrated core-log zoning workflow, Southwest Iran

Porosity estimation is a critical challenge in carbonate reservoir characterization due to complex pore systems and heterogeneity. This study compares core-derived and log-calculated porosity measurements in a carbonate reservoir in Southwest Iran at depths of 3250–3750 m, addressing industry challenges of data reliability and cost efficiency. While core analysis yields direct porosity measurements, its high cost and limited spatial coverage necessitate reliable log-based alternatives. The research utilized neutron, density, and acoustic logs to calculate porosity through established petrophysical relationships, comparing results with core data from 648 samples. Two innovative zoning approaches were developed: depth- and lithology-based zoning identified five distinct reservoir intervals, while porosity-based zoning classified the reservoir into three quality classes. Results show strong agreement between methods; log-derived mean porosity of 15 % closely matches the core measurement average of 12 %. Neutron-density logs effectively capture total porosity, while acoustic logs indicate primary porosity, enabling secondary porosity quantification. A key achievement is the implementation of Geolog software's deterministic and probabilistic methods to minimize interpretation subjectivity, reducing reliance on extensive coring while maintaining accuracy. The depth-based zoning approach identified high-quality reservoir intervals between 3450 and 3550 m with porosity exceeding 20 %. This work advances previous studies by offering: (1) a validated protocol for log-core integration in heterogeneous carbonates, (2) quantitative assessment of secondary porosity, and (3) practical zoning methodologies for reservoir quality prediction. Future research should focus on machine learning (ML) applications to enhance porosity prediction models and integrate advanced logging tools for improved fracture porosity characterization. • Log-core porosity match at 1.5 % MAE using novel depth-dependent correction for carbonate reservoirs. • Fracture Porosity Index (FPI) - First log-derived metric quantifying fracture impact on permeability. • Reservoir Quality Score (RQS) integrates porosity, fractures & shale to predict production zones. • Geolog software workflow reduces coring by 40 % while maintaining petrophysical data accuracy. • Zone 3 contains 20 % fracture porosity - Key high-productivity interval in heterogeneous carbonates.