Large-scale natural fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrops

Rahul Prabhakaran*, J. L. Urai, G. Bertotti, C. Weismüller, D.M.J. Smeulders

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
121 Downloads (Pure)

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.

Original languageEnglish
Article number104405
Number of pages20
JournalJournal of Structural Geology
Volume150
DOIs
Publication statusPublished - 2021

Keywords

  • Carbonates
  • Discrete fracture networks
  • Fractured pavements
  • Graph theory
  • Natural fracture networks
  • Spatial graphs

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