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Article
Electrofacies Characterization of an Iraqi Carbonate Reservoir

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Abstract

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs. The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MCA) depending on available well logs data for four wells from an Iraqi carbonate oil field. The optimum E-Facies units came from comparing them with geologist classification units for these four wells. Also, we conclude that the value of permeability is not important to get the optimum E-Facies units. Several runs have been tried each with different number of units using the Electro-Facies approach. The results of the techniques show very good match of the tops for various units with the actual ones. This application also shows the power and versatility of electrofacies characterization in improving reservoir descriptions in complex carbonate reservoirs


Article
Selection of Optimum Permeability Estimation Approach in a Heterogeneous Carbonate Reservoir

Authors: Mohsen Saemi --- Ali Mohammad Bagheri
Journal: Journal of Petroleum Research & Studies مجلة البحوث والدراسات النفطية ISSN: 22205381 Year: 2016 Volume: 272 Issue: 13 Pages: 143-153
Publisher: Ministry of Oil وزارة النفط

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Abstract

Determination of permeability is an essential component of reservoir characterization process which is among the key input parameters into a flow simulation models. Permeability modeling in carbonate reservoirs is still a challenge in the world. Permeability is directly determined in the laboratory from core analysis. Alternatively, it can be determined by analyzing well test or well logs. Due to high cost associated with coring and some technical problems, few wells in any given field are cored whereas most wells have wire-line logs. In this study detailed core analysis data including core porosity and core permeability supplemented by well logs and well test data to predict a continuous log derived permeability in un-cored wells in a heterogeneous carbonate reservoir in south west of Iran. The Mishrif reservoir in the studied field consists of limestone and interbedded shale. The field has 3 wells that have recovered cores. Permeability prediction was applied by several methods including: fuzzy logic, neural networks, clustering, empirical methods and regression analysis. These different methods were used to determine the optimal approach for utilizing in the field under study. To test the permeability prediction, the techniques were calibrated in 2 cored wells and blind tested in remaining cored well to see how well estimated permeability fitted the actual core permeability. Among all permeability modeling methods applied in the field, it turned out that electrofacies method and after that artificial neural network have the highest degree of association. Fuzzy logic and regression techniques are average in modeling permeability and empirical methods are not capable for predicting permeability in studied heterogeneous carbonate reservoir. The core analysis from 3 cored-wells was applied to determine permeability in 51 un-cored wells.

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