Open AccessProcessing outcrop point clouds to 3D rock structure using open source software
Author(s) -
Qian Liu,
Lisa Wronski,
Philipp Danzl
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/833/1/012054
Subject(s) - stereographic projection , point cloud , hough transform , computer science , point (geometry) , point location , software , kernel (algebra) , set (abstract data type) , point source , computer graphics (images) , artificial intelligence , algorithm , computer vision , geometry , mathematics , image (mathematics) , optics , combinatorics , physics , programming language
This study proposes a processing procedure to extract the 3D rock structure directly from point clouds using open source software. The basic processing involves: (1) estimating the Hough’s normal of each point; (2) converting the normal to dip direction and dip of the corresponding plane; (3) coloring each point in HSV color space according to its normal; (4) decoding the sets number using the multivariate kernel density estimators; (5) extracting and visualizing the set-based points; and (6) estimating the set-based geometric parameters and conducting stereographic projection. The result is an actual discrete fracture network aggregated with the set-based point clouds having HSV colors. From the initial point cloud to the completion of processing, we manage all data in one single file. The case studies show that the processing procedure can identify, extract, and quantify the fracture sets that have less exposed areas, which facilitates the evaluation of main risks.