Advanced Discontinuity Detection Algorithm for Geological Formations Using High-Density Point Cloud Data

Advanced Discontinuity Detection Algorithm for Geological Formations Using High-Density Point Cloud Data Antonin Chale, Michel Jaboyedoff, Marc-Henri Derron Geological hazard analysis relies on precise identification and characterization of discontinuities in rock formations, crucial for evaluating rock stability. While techniques such as Structure-from-Motion (SFM) and Light Detection and Ranging (LiDAR) have significantly advanced high-density 3D point cloud (PC) data acquisition, detecting structural irregularities in complex geological formations remains a challenge. We have developed a new discontinuity detection algorithm that emulates human visual perception. The algorithm employs multi-angle scanning, point cloud optimization techniques, and efficient multiprocessing to comprehensively survey the point cloud. Density maps are generated to identify and determine the orientation of discontinuities, proving effective in both synthetic models and real LiDAR data. The algorithm comprises three primary steps: an initial point cloud scan, density map generation, and visualization of discontinuities with their initial orientation. A secondary scan focuses on the density map, projecting data into a 2D representation to detect a second vector orientation, crucial for identifying discontinuity sets. Thanks to the previous steps we can deduce the orientation of the discontinuity sets. While the algorithm’s capability to handle both synthetic and real-world data sets highlight its potential significance in structural analysis, ongoing work aims to enhance its applicability for larger and more complex datasets. But also, the possibility of extracting the points involved in the different discontinuity sets.   References: Adrián J. Riquelme, A. Abellán, R. Tomás, M. Jaboyedoff, (2014)  " A new approach for semi-automatic rock mass joints recognition from 3D point clouds," Computers & Geosciences, Volume 68, 2014, Pages 38-52. Matthew J. Lato, Malte Vöge, (2012) "Automated mapping of rock discontinuities in 3D lidar and photogrammetry models," International Journal of Rock Mechanics and Mining Sciences, Volume 54, 2012, Pages 150-158.