Permeability Prediction Using Different Methods in Carbonate Reservoir

Abstract

This study aims to predict Yamama layers formation permeability of five wells: N1, N2, N3, N4, and N5, each containing Yamama, Yamama B and Yamama C layers. The permeability was calculated through two methods, namely the basic analysis and well-log techniques. The basic analysis method was conducted in the laboratory using a PERL-200 device. The results obtained using this method were more accurate as they matched the well-log results. Employing Matlab software, a neural network predicted permeability for 14 layers of 5 wells, with the second and fifth wells having only two layers. By constructing a 13-layer neural network, an appropriate network configuration can be achieved to discover the relationship between the input and output and produce a matching target result.