EXTRACTING AND COMPILING FRACTURE ATTRIBUTES FROM 3D OUTCROP MODELS

Standard methods for documenting rock fractures typically rely on direct measurements from outcrops. Unfortunately, these outcrop-based methods can be time-consuming and cannot be employed on hazardous and other difficult-to-access outcrops. High-resolution surveying methods, such as lidar and photogrammetry, enable the rapid creation of georeferenced 3D models of outcrops for digital mapping and analysis. We have developed a workflow that uses fractures mapped on these 3D models to efficiently calculate fracture attributes. This method allows users to define specific locations and analysis parameters, enabling the user to make decisions similar to those that would be made for field-based measurements, but with improved data processing speed. Our Python-based scripts, designed to integrate with ArcGIS geoprocessing tools, employ a spherical sampling method as an alternative to the traditional circular scanline approach used in field-based fracture measurements. The primary script generates a sphere at a user-defined radius to calculate fracture intensity, density, and mean trace length at each sample location. A supplementary script extends this method by measuring these attributes across a range of sphere radii, allowing users to examine how variations in radius influence the resulting fracture attributes. A separate script analyzes fracture orientations with customizable options for input parameters, analysis, and output products. Each fracture attribute measurement retains the sampling location, enabling spatial mapping of these attributes across the outcrop and analysis of attribute variability. By replicating the field methods in our digital workflow, we ensure that fracture attribute measurements can be directly compared between methods. Combining the 3D outcrop model, digitally mapped fractures, and the measured fracture attributes, provides a rich data archive that is well-suited for publication and future re-use.