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Comparative and Statistical Analysis of Core-Calibrated Porosity with Log-Derived Porosity for Reservoir Parameters Estimation of the Zamzama GAS Field, Southern Indus Basin, Pakistan

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Abstract

An accurate estimation of reservoir parameters such as porosity from conventional petrophysics has always been a challenging task for petrophysicists. These inaccuracies can be minimized by incorporating the standardized results obtained from the well-core information for continuous and precise estimates. The goal of the current study is to determine the most appropriate porosity estimation using reliable statistical approaches for the computation of precise reservoir parameters. In this study, characterization of porosity is carried out using root mean squared error and coefficient of variation. Total porosity (\(\phi_{{{\text{NDS}}}}\)) has minimum root mean squared error and coefficient of variation as compared to other porosity estimates. The minimum root mean squared error and coefficient of variation lead to a good prediction model with smaller residuals. In Zamzama-02 Well, the total porosity (\(\phi_{{{\text{NDS}}}}\)) for Pab Formation was derived from the average values of neutron, density and sonic logs data with lower values RMSE (2.81%), and the smaller coefficient of variation (31.48%). Subsequently, the estimated values were calibrated with core-derived porosity and permeability of Pab Formation. This comparison indicates existence of good correlation (R2 = 0.70). Therefore, the computed \(\phi_{{{\text{NDS}}}}\) provides more accurate results of different reservoir parameters including effective porosity, water saturation, and hydrocarbon saturation compared to porosities derived from conventional petrophysics.

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Acknowledgements

We extend our gratitude to Directorate General Petroleum Concession (DGPC), Pakistan, for the provision of Well Logs Data for this research and granting permission for using laboratory data. We thankful to ACS Laboratories, Brisbane and Hydrocarbon Development Institute of Pakistan for providing laboratory facilities. We are also indebted to LMKR Pakistan for facilitating data and software support. This study is funded by the Higher Education Commission, Pakistan, under Grant No. 20-14925/NRPU/R&D/HEC/2021/2020.

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  1. Department of Earth and Environmental Sciences, Bahria University, Islamabad, Pakistan

    Muhammad Nofal Munir, Mohammad Zafar & Muhsan Ehsan

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  1. Muhammad Nofal Munir
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Correspondence to Muhsan Ehsan.

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Munir, M.N., Zafar, M. & Ehsan, M. Comparative and Statistical Analysis of Core-Calibrated Porosity with Log-Derived Porosity for Reservoir Parameters Estimation of the Zamzama GAS Field, Southern Indus Basin, Pakistan. Arab J Sci Eng 48, 7867–7882 (2023). https://doi.org/10.1007/s13369-022-07523-9

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