Exploration of Kastification and Characterization Based on Borehole Image
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Published:2022-12-07
Issue:24
Volume:12
Page:12535
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Liu Wenlian,Sui Sugang,Xu Hanhua,Huai Yigao,Wang Jinchao,Zhao Jing
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.
Funder
National Natural Science Foundation for the Youth of China
Natural Resources Research Project of Hubei Province
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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