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

Том 18, Выпуск 5, 2015, pp. 507-518
DOI: 10.1615/JPorMedia.v18.i5.40
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Краткое описание

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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