An automated fracture trace detection technique using  the complex shearlet transform

Prabhakaran, Rahul; Bruna, Pierre-Olivier; Bertotti, Giovanni; Smeulders, David

doi:https://doi.org/10.5194/se-10-2137-2019

Articles | Volume 10, issue 6

https://doi.org/10.5194/se-10-2137-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/se-10-2137-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 6

Research article

|

20 Dec 2019

Research article |

| 20 Dec 2019

An automated fracture trace detection technique using the complex shearlet transform

Rahul Prabhakaran, Pierre-Olivier Bruna, Giovanni Bertotti, and David Smeulders

Data sets

Fracture Network Patterns from the Brejões Outcrop, Irecê Basin, Brazil R. Prabhakaran, Q. Boersma, F. H. R. Bezerra, and G. Bertotti https://doi.org/10.4121/uuid:67cde05c-9e99-4cc4-8cec-9f2666457d1f

Fracture Network Patterns from the Parmelan Anticline, France R. Prabhakaran, P.-O. Bruna, D. Smeulders, and G. Bertotti https://doi.org/10.4121/uuid:3f5e255f-edf7-441f-89f2-1adc7ac2f7d1

Model code and software

rahulprabhakaran/Automatic-Fracture-Detection-Code(supplement to Solid Earth Manuscript se-2019-104) R. Prabhakaran https://doi.org/10.5281/zenodo.3245452

Short summary

This contribution describes a technique to automatically extract digitized fracture patterns from images of fractured rock. Digitizing fracture patterns, accurately and rapidly with minimal human intervention, is a desirable objective in fractured rock characterization. Our method can extract fractures at varying scales of rock discontinuities, and results are presented from three different outcrop settings. The method enables faster processing of copious amounts of fractured outcrop image data.