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A New Technique to Estimate the Hydrocarbon Saturation in Shaly Formations: A Field Example in the Bahariya Formation, Egypt

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Soft Computing for Reservoir Characterization and Modeling

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 80))

Abstract

For many years, low resistivity formations were of little interest. Well logging pioneering research was hinged on the principle that hydrocarbon-filled rocks have a higher resistivity value than that of water-filled rocks. Through the years, it was found that many of the low resistivity formations were water-free oil producers. This triggered hundreds of research works devoted to study, characterize, and model these low resistivity hydrocarbon-bearing formations. These research works resulted in a series of empirical and theoretical models used to estimate the hydrocarbon saturation in such low resistivity formations.

The present study sheds light on the reasons for this feature with a special reference to the most common models used to calculate the hydrocarbon saturation in shaly formations. In order to choose the most representative shaly model that can be applied for a certain formation, the log analyst would need a reference that reflects the actual distribution of hydrocarbon saturation to which all the above shaly models can be compared. A new technique to which the different shaly models can be compared is developed by the aid of well logs and special core analysis.

The application of this new technique and the selection of the most appropriate shaly model were applied on Bahariya formation, in the western desert of Egypt, that is characterized by the presence of clay minerals, which lower its resistivity. The results of this application reveal the high accuracy of this technique and the superiority of the CYBERLOOK model, among the different shaly models that were used in this study.

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Dawood, A.M., Ibrahim, A.A., El-Tayeb, ES.A. (2002). A New Technique to Estimate the Hydrocarbon Saturation in Shaly Formations: A Field Example in the Bahariya Formation, Egypt. In: Wong, P., Aminzadeh, F., Nikravesh, M. (eds) Soft Computing for Reservoir Characterization and Modeling. Studies in Fuzziness and Soft Computing, vol 80. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1807-9_12

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  • DOI: https://doi.org/10.1007/978-3-7908-1807-9_12

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2495-7

  • Online ISBN: 978-3-7908-1807-9

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