Characterization of Porosity Properties of Carbonate Rocks through a Fast Image Processing Approach

Resumo

The characterization of porous media represents a critical issue for recovering oil and gas from reser-
voir rocks. Analyses of digital images generated by X-ray micro-computed tomography (μCT) help build detailed

models of rocks and extract petrophysical parameters. For this purpose, we have developed an efficient 2D mi-
crotomographic image processing method for the extraction of samples’ porous system properties. The proposed

method utilizes a histogram-based analysis to perform the segmentation of the images. Our approach allows the

automatic computation of the total porosity, pore size distribution, and general pore orientation data of seven lime-
stone plugs from the Eocene Tambaba Formation by the usage of image processing techniques. The porosity values

extracted by the new segmentation technique were compared against porosity values obtained through porosime-
try (helium) essays. The average error between experimental values (obtained by porosimetry) and the porosity

values obtained through the proposed segmentation process is 3,42%. A comparison of pore orientation distri-
bution provided automatically by the proposed technique and the orientation obtained through classical methods

showed excellent correlation. Computation time spent for the automatic calculation of pore system properties was

approximately 9 minutes per sample (performed in an Intel Core i7 CPU with 8GB of RAM PC). Further experi-
ments of calculations with smaller quantities of slices provided similar petrophysical properties, with a reduction

of 95.7% on the processing time. The accomplished results showed the new automatic segmentation technique’s
great potential for the extraction of porous system properties of calcareous rocks with accuracy and efficiency in
computational time.