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Exploration of Kastification and Characterization Based on Borehole Image

Authors :
Wenlian Liu
Sugang Sui
Hanhua Xu
Yigao Huai
Jinchao Wang
Jing Zhao
Source :
Applied Sciences, Vol 12, Iss 24, p 12535 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

The characteristics of the karst pore structure not only affect the seepage features of the rock mass in the karst area but also have a noticeable effect on the mechanical behavior in the process of rock mass loading. The exploration of the exhibition karst pore structure plays a crucial role in the development of science, technology, and engineering construction. In order to appropriately unlock the problem of image brightness imbalance caused by probe eccentricity in field image acquisition and to realize the proper in situ identification and precise characterization of the borehole structure, the scrutiny of karst pore recognition and a characterization method based on the borehole image are proposed. First, combined with the imaging characteristics of borehole image construction, an eccentric image acquisition model is constructed, the change law of image illumination intensity is clarified, and a suitable pretreatment method is developed for karst pore structures, which effectively enhances the borehole image quality. Subsequently, the pore structure identification method is established by integrating the gradient operator and the maximum interclass variance method, which could successfully screen and filter out the non-porous region segments and ensure that the identified pore structure features are more accurate and rich. Finally, on the basis of representing the single pore structure, number and area proportion functions are constructed in both the depth and azimuth directions, and the distribution characteristics of the pore structure on the borehole wall are evaluated in various dimensions. The achieved results reveal that the proposed pore structure identification and characterization approach could substantially enhance the work efficiency of the karst pore structure in borehole images and provide a simple, reliable, and effective method for the statistics and application of karst pore data.

Details

Language :
English
ISSN :
12241253 and 20763417
Volume :
12
Issue :
24
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.7359167f801c45e894ac354487d4d45f
Document Type :
article
Full Text :
https://doi.org/10.3390/app122412535