Determination of rock typing in one of carbonate reservoirs in South of Iran by using of MRGC method and hydraulic flow

Abstract

Find the productive zones in carbonate reservoirs are challenging issues in the petroleum industry. In this study, Determination of Rock Typing by help of petrophysical rock typing (determine electrofacieses type) described by Multi-Resolution Graph-based Clustering method and classification of hydraulic flow. Mechanism of this study is that using of Neural Network, permeability determined in studied reservoir at desired intervals withdata obtained by core simulation and FZI. Then in the next step, by using Matlab software, FZI Clustering was done. According to the core data, seven clusters has been selected for the reservoir. Clusters obtained in this way, as the diagram along MRGC method was also assessed. In continuation of the study of MRGC method, the cluster with 7 Electrofaciese was selected. The results of clustering by MRGC and HFU methods, has shown very satisfactory compliance with the interpretation of the results of petrophysical logs and core analysis. Using these two categories, reservoir zones measured and productive zones are separated from non-productive, and comparing together. The results show that the overlap rate of determining facieses of the reservoir and non-reservoir zones, relative to each other in both ways is very convincing and good.