Investigating the vertical and lateral heterogeneity in an Iranian carbonate reservoir using advanced petrophysical logs, petrographic data and image processing techniques.
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| Title: | Investigating the vertical and lateral heterogeneity in an Iranian carbonate reservoir using advanced petrophysical logs, petrographic data and image processing techniques. |
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| Authors: | Yarmohammadi, Saeed1 (AUTHOR) syarmohammadi@aut.ac.ir, Javaherian, Abdolrahim1 (AUTHOR) javaherian@aut.ac.ir, Sharifi, Mohammad1 (AUTHOR) m_sharifi@aut.ac.ir, Saberi, Mohammad Reza2 (AUTHOR) saberi.rp@gmail.com, Basir, Hadi Mahdavi1 (AUTHOR) basir.m@aut.ac.ir |
| Source: | Journal of Petroleum Exploration & Production Technology. Sep2025, Vol. 15 Issue 9, p1-19. 19p. |
| Abstract: | Carbonate formations, known for their complex characteristics, require detailed internal heterogeneity knowledge for effective exploration and production. This study presents an integrated workflow to investigate heterogeneity at different scales, from microscopic to log level, in southwest Iran wells. Geological settings were studied, including depositional systems, structural elements, field stresses, diagenesis, and facies variations. Conventional petrophysical evaluation determined lithologies, porosity, and fluid types/content. Statistical methods such as Lorenz curves, semivariance analysis, and the coefficient of variation were used to analyze porosity heterogeneity. Image processing (segmentation) analyzed petrographic images to identify rock matrix and pore spaces. Image logs from oil-based microimagers and ultrasonic borehole imagers showed variations in porosity, fracture networks, zonation, and stress directions. Nuclear magnetic resonance log provided porosity types and sizes. We evaluated vertical and lateral heterogeneities across different zones and wells. This study’s results show that a multi-scale workflow is essential for accurately characterizing reservoir heterogeneity in carbonate fields. The analysis effectively identifies sedimentological and structural influences, quantifies heterogeneity, and ranks zones based on their heterogeneity. The models developed through this workflow enhance decision-making in reservoir characterization and offer practical applications for field studies. Despite limitations like imaging resolution and data availability, this approach remains integral to advancing the understanding of heterogeneity and guiding further improvements. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | Carbonate formations, known for their complex characteristics, require detailed internal heterogeneity knowledge for effective exploration and production. This study presents an integrated workflow to investigate heterogeneity at different scales, from microscopic to log level, in southwest Iran wells. Geological settings were studied, including depositional systems, structural elements, field stresses, diagenesis, and facies variations. Conventional petrophysical evaluation determined lithologies, porosity, and fluid types/content. Statistical methods such as Lorenz curves, semivariance analysis, and the coefficient of variation were used to analyze porosity heterogeneity. Image processing (segmentation) analyzed petrographic images to identify rock matrix and pore spaces. Image logs from oil-based microimagers and ultrasonic borehole imagers showed variations in porosity, fracture networks, zonation, and stress directions. Nuclear magnetic resonance log provided porosity types and sizes. We evaluated vertical and lateral heterogeneities across different zones and wells. This study’s results show that a multi-scale workflow is essential for accurately characterizing reservoir heterogeneity in carbonate fields. The analysis effectively identifies sedimentological and structural influences, quantifies heterogeneity, and ranks zones based on their heterogeneity. The models developed through this workflow enhance decision-making in reservoir characterization and offer practical applications for field studies. Despite limitations like imaging resolution and data availability, this approach remains integral to advancing the understanding of heterogeneity and guiding further improvements. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 21900558 |
| DOI: | 10.1007/s13202-025-02057-w |
