Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 14
Articles | Volume 18, issue 14
https://doi.org/10.5194/gmd-18-4469-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-4469-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 14
Model description paper
 | 
23 Jul 2025
Model description paper |  | 23 Jul 2025

SubsurfaceBreaks v. 1.0: a supervised detection of fault-related structures on triangulated models of subsurface homoclinal interfaces

Michał P. Michalak, Christian Gerhards, and Peter Menzel

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Short summary
Using geometric features of synthetic triangulated models of subsurface homoclinal interfaces, we applied machine learning to detect faults. Testing on real borehole data validated its effectiveness across various fault orientations. The supervised approach represents a significant improvement over older methods that relied on simpler clustering techniques which were capable of identifying fewer orientations of potential faults.
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