2026-06-10T05:19:38Zhttp://doidb.wdc-terra.org/oaip/oaioai:doidb.wdc-terra.org:71262022-02-24T15:30:08ZDOIDBDOIDB.GFZfalse4DOIDB.GFZ
10.5880/GFZ.2.5.2021.001
Wrona, Thilo
Thilo
Wrona
0000-0002-9707-0595
GFZ German Research Centre for Geosciences, Potsdam, Germany
Pan, Indranil
Indranil
Pan
0000-0002-9624-5146
Imperial College London, London, UK
Bell, Rebecca
Rebecca
Bell
0000-0002-4785-9707
Imperial College London, London, UK
Gawthorpe, Robert
Robert
Gawthorpe
0000-0002-4352-6366
University of Bergen, Bergen, Norway
Fossen, Haakon
Haakon
Fossen
0000-0002-8091-5643
Museum of Natural History/Department of Earth Science, University of Bergen, Bergen, Norway
Brune, Sascha
Sascha
Brune
0000-0003-4985-1810
GFZ German Research Centre for Geosciences, Potsdam, Germany
3-D seismic interpretation with deep learning: a set of Python tutorials
GFZ Data Services
2021
Seismic reflection data
Seismic interpretation
Machine learning
Deep learning
Geophysics
EARTH SCIENCE
EARTH SCIENCE > OCEANS > MARINE GEOPHYSICS
EARTH SCIENCE > SOLID EARTH > TECTONICS
Wrona, Thilo
GFZ German Research Centre for Geosciences, Potsdam, Germany
Software
10.31223/X5S88B
0.1
CC0 Universal 1.0
Here we are sharing our code, tutorials and examples used to interpret geological structures (e.g. faults, salt bodies and horizones) in 2-D and/or 3-D seismic reflection data using deep learning. The repository is organised in a series of tutorials (Jupyter notebooks) with increasing degree of difficulty. We show step-by-step how to: (1) load seismic data, (2) train a model and (3) apply the model to map different geological structures. You can find a few visual examples on our poster and more technical details in our preprint.
The Norwegian Academy of Science and Letters
6269
Helmholtz-Gemeinschaft
http://doi.org/10.13039/501100001656
AdvancedEarth System Modelling Capacity (ESM)
Geo.X Network