Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

Thiele, Samuel T.; Grose, Lachlan; Samsu, Anindita; Micklethwaite, Steven; Vollgger, Stefan A.; Cruden, Alexander R.

doi:https://doi.org/10.5194/se-8-1241-2017

Articles | Volume 8, issue 6

https://doi.org/10.5194/se-8-1241-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/se-8-1241-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 8, issue 6

Method article

|

21 Dec 2017

Method article |

| 21 Dec 2017

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

Samuel T. Thiele, Lachlan Grose, Anindita Samsu, Steven Micklethwaite, Stefan A. Vollgger, and Alexander R. Cruden

Data sets

GeoTrace and Compass rapid trace-mapping (example data) S. Thiele, S. Vollgger, and A. Samsu https://doi.org/10.4225/03/5981b31091af9

Model code and software

GeoTrace L. Grose and S. Thiele https://doi.org/10.5281/zenodo.1052869

Short summary

We demonstrate a new method that enhances our ability to interpret large datasets commonly used in the earth sciences, including point clouds and rasters. Implemented as plugins for CloudCompare and QGIS, we use a least-cost-path solver to track structures and contacts through data, allowing for expert-guided interpretation in a way that seamlessly utilises computing power to optimise the interpretation process and improve objectivity and consistency.