Study of Pore Types Influence for Permeability Value in Carbonate Reservoir Using Differential Effective Medium (DEM) and Adaptive Neuro-Fuzzy Inference System Algorithm

Abstract

The pore system in a carbonate reservoir is very complex compared to the pore system in clastic rocks. According to measurements of the velocity of propagation of sonic waves in rocks, there are three types classification of carbonate pore classifications: Interparticle, Vugs and Crack. The complexity of these pore types can lead to errors in the calculation or interpretation of the reservoir itself so that characterization of the carbonate reservoir tends to be more difficult.

In this research, elastic modulus modeling will be carried out by taking into account the pore complexity of the carbonate reservoir. Differential Effective Medium (DEM) is an elastic modulus modeling method that takes into account the heterogeneity of pores in the carbonate reservoir. This method adds pore type inclusions gradually into the host material to the desired proportion of the material. In addition, this study will also predict the permeability value of the reservoir using Adaptive Neuro-Fuzzy Inference System algorithm from well logging measurement data as the input and core data from laboratory measurements for training data and validating the predicted results of permeability values in well depths domain. So, the permeability value and pore type variations in well depth domain will be obtained for further interpretation.

Thus we can see which type of pore has a good permeability value in the carbonate reservoir. This kind of thing can also help the engineers to determine a good perforation zone in the well by considering the pores type in the carbonate reservoir and the permeability values that have been predicted before.