Rock joint detection from borehole imaging logs based on grey-level co-occurrence matrix and Canny edge detector

Abstract

Rock joints play an important role in characterizing the rock mass quality for geo-mechanical design and stability analysis. An approach was developed to detect and characterize the rock joints from images collected by a borehole imaging system. A gray-level co-occurrence matrix was employed to locate the joint regions, allowing more focused and effective detection processing, followed by extractions of the upper and lower edges of rock using the Canny algorithm. Four basic geometrical parameters of rock joints－orientation, depth, aperture, and core length－were determined based on the fitting of sinusoids to joints’ edges. Furthermore, the joint density was determined based on the geometric parameters. To calibrate the proposed approach, a borehole in the Rumei hydropower station engineering at Lantsang River was selected as a case study. Orientation of rock joints with gentle dip angles, which was determined from borehole imaging logs, corresponded to the measurement in three horizontal tunnels. Additionally, both joint density and pressure-wave velocity revealed that jointed rock mass was observed in the depth from 100 m to 120 m, and intact rock mass was presented in the depth of 150 m to 170 m, indicating the good performance of the proposed method.