Prediction of Sedimentary Features in Asmari Formation, SW of Iran: Using Electrofacies Analysis

Authors

1 Department of Geology, Faculty of Earth Sciences., ShahidChamran University, Ahvaz

2 NIOC, Ahvaz

Abstract

     One of the most important elements in reservoir characterization is mapping of the features and heterogeneities of the reservoir. In heterogeneous carbonate reservoirsdue to presence of high complexity and heterogeneity, the porosity and permeability distribution is diverse and ambiguous. Accordingly, use of modern methods in improved assessment of these reservoirs would be essential. Among these approaches, identification and application of Electrofacies (Log Facies) has been considered as one of the most important methods in production of reservoirs as well as development of the Oilfields.The present work is devoted to utilize Self Organization Map (SOM) mode in neural network to clustering electrofacies of Asmari Formation in one of the oil field in southwest Iran. The Electrofacies reservoir quality shows that EF1 and EF5 appear to have the best reservoir characteristics, followed by EF2 and EF6. By contrast, Electrofacies 3, 4 and 7 show poor reservoir quality. Cited facies correlated with Petrographical features to relate carbonate and sandstone sedimentary fabrics with pore space size distribution and petrophysical characteristics of electrofacies in studied wells. Totally the defined facies show well correlation with petrography of the analyzed intervals and hence the electrofacies defined in this study could be considered as replacement of sedimentary ones and propagated to all wells of this field.
 

Keywords

References

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