Articles | Volume 12, issue 10
https://doi.org/10.5194/se-12-2159-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-12-2159-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Sep 2021
Research article |
| 30 Sep 2021
| 30 Sep 2021
Investigating spatial heterogeneity within fracture networks using hierarchical clustering and graph distance metrics
Rahul Prabhakaran
CORRESPONDING AUTHOR
Department of Geoscience and Engineering, Delft University of Technology, Delft, the Netherlands
Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
Giovanni Bertotti
Department of Geoscience and Engineering, Delft University of Technology, Delft, the Netherlands
Janos Urai
Structural Geology, Tectonics and Geomechanics, RWTH Aachen University, Aachen, Germany
David Smeulders
Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
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Short summary
Rock fractures are organized as networks with spatially varying arrangements. Due to networks' influence on bulk rock behaviour, it is important to quantify network spatial variation. We utilize an approach where fracture networks are treated as spatial graphs. By combining graph similarity measures with clustering techniques, spatial clusters within large-scale fracture networks are identified and organized hierarchically. The method is validated on a dataset with nearly 300 000 fractures.
Rock fractures are organized as networks with spatially varying arrangements. Due to networks'...
