Open AccessRock surface porosity measurement and pore distribution analysis based on hole wall images
Author(s) -
Chunling Wang,
C Y Wang,
Zhengsheng Han,
Y T Wang,
Yingsong Huang
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/570/6/062037
Subject(s) - porosity , binary image , basis (linear algebra) , characterisation of pore space in soil , materials science , image (mathematics) , image processing , image segmentation , geology , artificial intelligence , mineralogy , geometry , computer science , mathematics , composite material
This study proposes a method that uses image processing technology to identify, calculate, and analyze the pore structure in hole wall images. First, the R, B, and G components of a hole wall image are adjusted on the basis of an appropriate threshold to eliminate the effects of drilling fluid attached to the hole wall. Second, the hole wall image is converted into an S component image in the HSV color space to distinguish the pores and dark gray texture of the rock. Third, the best segmentation threshold of the S component image is obtained by the maximum interclass variance method, and the threshold is used to binarize the S component image. Finally, mathematical morphological operations are performed on the binary image to eliminate defects. On the basis of the identified pore structure in the hole wall image, the surface porosity of the rock can be calculated, and the pore distribution characteristics can be further analyzed. The results of this work provide ideas for measuring the porosity of deep rocks and analyzing their pore distribution.