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Journal of Porous Media
IF: 1.061 5-Year IF: 1.151 SJR: 0.504 SNIP: 0.671 CiteScore™: 1.58

ISSN Print: 1091-028X
ISSN Online: 1934-0508

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Journal of Porous Media

DOI: 10.1615/JPorMedia.v18.i5.40
pages 507-518

PORE, THROAT, AND GRAIN DETECTION FOR ROCK SEM IMAGES USING DIGITALWATERSHED IMAGE SEGMENTATION ALGORITHM

Amirhossein Tavanaei
The Center for Advance Computer Studies, University of Louisiana at Lafayette, LA 70504
Saeed Salehi
Petroleum Engineering Department, University of Louisiana at Lafayette, LA 70504

ABSTRACT

Estimation of rock porosity by automatic and fast methods is one of the critical challenges in recent studies due to its importance in formation properties and prediction of other parameters. This paper proposes a method to separate pores, grains, and throats in scanning electron microscope (SEM) images. The method utilizes a digital image segmentation algorithm to distinguish the pores and their connections from grains. The proposed method is called watershed image segmentation, which uses gradient image for pore detection. Furthermore, morphological concepts are applied in this algorithm to separate the grains, pores, and throats. In addition, as SEM images, like other data sources, are polluted by noise and lack of information in their pixel values, required digital image preprocessing is done to provide the highquality images and consequently desirable results. This investigation, in comparison with constant threshold based methods for pore detection, demonstrates the acceptable estimation in pore-grain recognition. Finally, porosity values of high perm and low perm sample rocks are calculated.


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