%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2020/10.01.00.16
%2 sid.inpe.br/sibgrapi/2020/10.01.00.16.44
%@doi 10.1109/SIBGRAPI51738.2020.00033
%T An efficient method for porosity properties extraction of carbonate rocks
%D 2020
%A Cardoso, Victor Gomes,
%A Barros, Edna Natividade da Silva,
%A Barbosa, José Antonio,
%A Antonino, Antonio Celso Dantas,
%A Nova, Abraćo Alves Vila,
%@affiliation Federal University of Pernambuco, Brazil
%@affiliation Federal University of Pernambuco, Brazil
%@affiliation Federal University of Pernambuco, Brazil
%@affiliation Federal University of Pernambuco, Brazil
%@affiliation Federal University of Pernambuco, Brazil
%E Musse, Soraia Raupp,
%E Cesar Junior, Roberto Marcondes,
%E Pelechano, Nuria,
%E Wang, Zhangyang (Atlas),
%B Conference on Graphics, Patterns and Images, 33 (SIBGRAPI)
%C Porto de Galinhas (virtual)
%8 7-10 Nov. 2020
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K µCT images, carbonate rocks and porosity properties.
%X Porous media characterization presents substantial importance for the oil industry. The X-ray micro-computed tomography (µCT) is often used to generate digital models of reservoir rocks. This paper presents an automatic histogram-based method for the segmentation of µ CT images, which allows the fast extraction of some petrophysical properties. The processing is based on the analysis of the typical 2D images used to produce 3D volumes. The method was applied to analyze seven samples of carbonate rocks, to define the porosity values, pores size distribution, and the orientation of the pores. Calculated porosity values were compared to the porosity results obtained with a helium porosimeter. The comparison of porosity calculated by this method against the experimental values showed an average error of 3.43%. The computational time spent for each sample processing was of about 9 minutes on a regular PC. The method can be used to extract porosity parameters in a large number of samples with a substantial gain of time and computational power.
%@language en
%3 Sibgrapi_2020_Main_Track_ID_111.pdf