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Permeability Prediction Enhancement in Carbonate Reservoirs by Proposing a New Fuzzy Logic Approach

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Author(s): S. Alfaouri | M. Ali Riahi | N. Alizadeh | M. Rezaei

Journal: Journal of Applied Sciences
ISSN 1812-5654

Volume: 9;
Issue: 18;
Start page: 3263;
Date: 2009;
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Keywords: Fuzzy logic | permeability prediction | Persian Gulf Carbonate reservoirs | Asmari formation | Sarvak formation

ABSTRACT
The aim of this study was to modify some previous Fuzzy based models for developing a convenient and robust method for permeability problem solving in carbonates. The proposed technique is tested in two complex giant Iranian oil fields for justification; which are Sarvak and Asmari formations. The results were much more precise than previous similar Fuzzy studies which were in high agreement with core measured values. Permeability values estimation using core-derived information of wells with just electric logs is an old problem in reservoir characterization. In essence, the problem consists in finding some explicit relation between log and core data in those wells that contain both types of information. Then, describe reservoir features (derived from core data) of wells with log information only. Fuzzy logic is one of the intelligent techniques that have been applied extensively nowadays, but all the previous researches in this subject have been applied in Sandy reservoir cases. In this study, besides the previous studies a new Fuzzy model has been testified to estimate permeability values in two carbonate reservoirs. Moreover, the accuracy of the predicted results will be considered comparing with the measured core values. During this study a new modification in defuzzification stage will be introduced to make the method much more accurate and flexible in predicting permeability values in carbonates. Results show that the new proposed method yields better estimations than similar previous techniques in carbonate reservoirs. Furthermore, the predicted results represented in the actual range of core plugs permeability measures.

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