Effect of CT Data Upscaling on Permeability Estimation ofCarbonate Samples

Permeability is one of the most important characteristics of hydrocarbon bearing formations. An accurate knowledge of permeability provides petroleum engineers with a tool for efficiently managing the production process of a field. Formation permeability is often measured in the laboratory from cores or evaluated from well test data. To carry out this study, 34 core samples from a carbonate oil field located in the south west of Iran have been considered. The Permeability of samples was measured using a PDPK™ apparatus, the porosity of each sample was measured and CT slices were taken in constant intervals across the samples. Thin sections in the horizontal and vertical directions were prepared from the end pieces of the samples and were analyzed by using the optical microscope. CT numbers corresponding to each slice were exported in the form of a spreadsheet. All such spreadsheets that belong to the i th sample, together with porosity and PDPK™ average permeability were called "i th data set". All data sets were considered as training examples of a back propagation artificial neural network, whilst the target was permeability. Validation of the network results was achieved by leaving out some of the data sets and comparing their measured permeabilities with calculated ones. To decrease calculation time, up scaling was applied on CT data by scales of 2:1, 4:1, 8:1, 16:1 and 32:1 and results were compared with each other. A better understanding of the relationship between volume percentage of minerals, porosity, CT scan data and permeability of carbonates is developed from this study.6