Structural interpretation of Digital Outcrop Models on point clouds using a semi-automatic workflow: case studies on fractured metamorphic rocks (Aosta Valley, Italy)
Authors: Casiraghi Stefano , Bistacchi Andrea , Agliardi Federico , Arienti Gloria , Monopoli Bruno , Dal Piaz Giovanni , Bertolo Davide 
Published: February 2023

The study and characterization of fracture network find applications in a wide range of fields, from the analysis and modelling of mechanical and hydraulic properties of rock masses, to petroleum reservoirs, waste repositories, aquifers and Carbon Capture and Sequestration (CCS). In this context, the use of Digital Outcrop Models (DOMs), overcame the limitations of the classic field survey, such as limited access and logistics, providing a solid framework for the collection of large and quantitative datasets. Here we present a semi-automatic workflow for DOMs structural interpretation, carried out on outcrops of fractured gneiss, prasinites and calcschist of the Dent-Blanche Nappe and Combin Zone, exposed on the Italian side of the Cervino/Matterhorn in Valtournenche. Our methodology is based on a combination of traditional field survey and remote sensing techniques (photogrammetry or laser scanning). The preliminary step is the selection of representative outcrops in terms of structural and lithological properties of a larger rock volume, based on a thorough knowledge of regional structural geology and tectonics; moreover, the outcrop must be representative in terms of morphology and orientation. At this stage it is important to select outcrops that have several faces (e.g. vertical face and a horizontal pavement), so it will be possible to evaluate both the orientation and height distribution on the vertical face and the length distribution on the horizontal &#8220;pavement&#8221;. The main purpose of the traditional field survey is the analysis of kinematics, relative chronology and mineralization - all parameters needed to characterize fracture sets in terms of their genesis and deformative evolution. At the same time, remote sensing dataset are collected and the output is a point cloud DOM (PC-DOM) colorized with RGB values. After a pre-processing phase where the PC-DOM is cleaned from edge noise (resulting from the photogrammetric processing), vegetation and debris (naturally present in most outcrops), orientation data are collected manually, using suitable software tools (e.g. Compass plugin in CloudCompare or PZero). This step allows, together with the results of the field survey, selecting different fracture sets and characterizing their orientation statistics. The second step consist in a manual segmentation of the PC-DOM based on the previous characterization of fracture sets. In the final step, data are automatically extracted using specific algorithm calibrated based on previous steps (e.g. FACETS plugin in CloudCompare). In the end, this workflow aims at maximizing data collection from DOMs to be used as a basis for the subsequent extraction of statistical parameters such as length and height distribution, orientation statistics, abutting and crosscutting relationship between different sets, connectivity, etc.