Prediction of Flow Units in Heterogeneous Carbonate Reservoirs Using Intelligently Derived Formula: Case Study in an Iranian Reservoir

Abstract

Several techniques for identifying and characterizing flow units of sandstone reservoirs have been proposed in the literature. The most established technique relies on the log–log plot of the reservoir quality index (RQI) versus the pore to matrix ratio (PMR). A straight line of slope unity across these points is extrapolated to PMR = 1 yielding the flow zone index (FZI). Samples that lie on the same straight line have similar pore throat characteristics and, therefore, constitute a flow unit; samples with different FZI values will lie on different parallel lines. In this study, this technique is extended to an Iranian carbonate reservoir. A genetic algorithm is employed to develop an empirical formula for predicting flow units in heterogeneous carbonate reservoirs. Conventional well log data as well as 410 core data, including porosity and permeability were available from the studied intervals. To establish the prerequisites for developing the intelligently derived formula, each set of the well log data was matched to its corresponding core data. Among them, 331 data points were used for developing the formula and 79 points verified the reliability of the obtained formula. The overall mean squared error and correlation coefficient between the logarithms of the measured and predicted FZI calculated through the respective formula for the test data are 0.1262 and 0.85, respectively. The results of the present study demonstrate the strength of the developed formula for predicting flow units of carbonate reservoirs. The proposed formula requires sonic, bulk density, deep laterolog, and corrected neutron porosity well logs.