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<p>Accurate water saturation (Sw) modeling in carbonate reservoirs remains a persistent challenge due to complex pore structures and facies heterogeneity that compromise the reliability of traditional resistivity-based techniques. This study introduces a high-resolution facies-based workflow for Sw estimation that integrates core-derived capillary pressure data, Nuclear Magnetic Resonance (NMR) log interpretation, and electrofacies classification using the Equivalent Flow Zone Indicator (EFZI) method. The approach was applied to two wells drilled through the Kangan-Dalan Formation, a carbonate interval characterized by wide variations in porosity and permeability. Saturation Height Functions (SHFs) were established using Leverett J-functions calibrated for ten distinct electrofacies, allowing for facies-dependent Sw profiling. The proposed methodology combines three independent saturation estimation techniques: resistivity-driven models, NMR-derived irreducible water saturation based on Transverse Relaxation Time (T₂) distributions, and SHF modeling. Statistical comparison demonstrated strong agreement between resistivity- and SHF-derived saturation values, with Regression (R²) values of 0.90 and 0.80 for Wells A and B, respectively, and low root mean square error. Additionally, calibration of the T₂ cutoff enhanced the accuracy of NMR interpretation, validated by production performance. The results confirm that the developed workflow significantly improves saturation modeling resolution, particularly in data-limited zones lacking resistivity or core information. The methodology enables real-time reservoir evaluation and is applicable to other carbonate systems with similar geological and petrophysical complexity. This study offers a robust solution to overcome the limitations of conventional saturation modeling approaches in complex reservoir environments.</p>

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An integrated approach to address the heterogeneity of carbonate gas reservoirs using high resolution saturation height function

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月3日

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  • Sirous Hosseinzadeh,
  • Behnam Esmaeili,
  • Ali Kadkhodaie,
  • Mostafa Sabouhi,
  • Zahra Salavati

摘要

Accurate water saturation (Sw) modeling in carbonate reservoirs remains a persistent challenge due to complex pore structures and facies heterogeneity that compromise the reliability of traditional resistivity-based techniques. This study introduces a high-resolution facies-based workflow for Sw estimation that integrates core-derived capillary pressure data, Nuclear Magnetic Resonance (NMR) log interpretation, and electrofacies classification using the Equivalent Flow Zone Indicator (EFZI) method. The approach was applied to two wells drilled through the Kangan-Dalan Formation, a carbonate interval characterized by wide variations in porosity and permeability. Saturation Height Functions (SHFs) were established using Leverett J-functions calibrated for ten distinct electrofacies, allowing for facies-dependent Sw profiling. The proposed methodology combines three independent saturation estimation techniques: resistivity-driven models, NMR-derived irreducible water saturation based on Transverse Relaxation Time (T₂) distributions, and SHF modeling. Statistical comparison demonstrated strong agreement between resistivity- and SHF-derived saturation values, with Regression (R²) values of 0.90 and 0.80 for Wells A and B, respectively, and low root mean square error. Additionally, calibration of the T₂ cutoff enhanced the accuracy of NMR interpretation, validated by production performance. The results confirm that the developed workflow significantly improves saturation modeling resolution, particularly in data-limited zones lacking resistivity or core information. The methodology enables real-time reservoir evaluation and is applicable to other carbonate systems with similar geological and petrophysical complexity. This study offers a robust solution to overcome the limitations of conventional saturation modeling approaches in complex reservoir environments.