Abstract
The Lilstock outcrop in the southern Bristol Channel provides exceptional exposures of several limestone beds displaying stratabound fracture networks, providing the opportunity to create a very large, complete, and ground-truthed fracture model. Here we present the result of automated fracture extraction of high-resolution photogrammetric images (0.9 cm/pixel) of the full outcrop, obtained using an unmanned aerial vehicle, to obtain a spatially extensive, full-resolution map of the complete fracture network with nearly 350,000 ground-truthed fractures. We developed graph-based functions to resolve some common issues that arise in automatic fracture tracing such as incomplete traces, incorrect topology, artificial fragmentation, and linking of fracture segments to generate geologically significant trace interpretations. The fracture networks corresponding to different regions within the outcrop are compared using several network metrics and the results indicate both inter- and intra-network (layer to layer) structural variabilities. The dataset is a valuable benchmark in the study of large-scale natural fracture networks and its extension to stochastic network generation in geomodelling. The dataset also highlights the intrinsic spatial variation in natural fracture networks that can occur even in weakly-deformed rocks over relatively short length scales of tens of metres.
Highlights
Fractures in rocks can form networks with fracture tips forming abutting or crossing physical interactions with other fractures or remaining isolated within rock matrix
The methods in Section.4 are applied to image tiles corresponding to the five selected areas and based on these we generate five large net works
The created fracture data are in the form of spatial graphs and shapefiles attached in the supplementary data
Summary
Fractures in rocks can form networks with fracture tips forming abutting or crossing physical interactions with other fractures or remaining isolated within rock matrix. Mechanistic numerical modelling of fracture propagation and sub sequent fracture network formation can include complex physics per taining to individual fractures such as fracture tip behaviour, fluid driven fracturing, interaction of propagating fractures with pre-existing discontinuities and other propagating fractures (Laubach et al, 2019) Such mechanistic models can be based on extended finite element methods (such as Remij et al, 2015; Valliappan et al, 2019 etc), discrete element methods (such as Virgo et al, 2016; Guo et al, 2017 etc), and phase-field methods (such as Yoshioka and Bourdin, 2016; Lepillier et al, 2020 etc), and differ in the way rock substrate and propagating fracture are numerically treated. Recent developments include approaches in which fracture networks genetically evolve from flaws without resorting to rigorous geomechanical treatment (such as Lavoine et al, 2020; Welch et al, 2019) but large-scale network development is still difficult to realize
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