Published August 5, 2024
| Version v1
Dataset
Open
Dataset and Code Accompanying "Challenges and Learning from Exploring Deep Metric Learning for Identifying Seismic Stratigraphy"
Authors/Creators
-
1.
University of Oslo
-
2.
Aker BP (Norway)
- 3. ConocoPhillips Norway
Description
Dataset and code related to the work outlined in "Challenges and Learning from Exploring Deep Metric Learning for Identifying Seismic Stratigraphy".
File Description:
- seis_seg.h5 - trained model weights.
- topseis_temp.npy - seismic survey.
- train_demo.ipynb - training demo including synthetic modelling pipeline.
- inference_and_plot - inference and reproducing main results.
Pre-calculated phase volume and encoded features for reproducing figures:
- unwrapped_phase_volume_full.npy.
- features_full_ds222_ps32_s222.npy.
- indices_full_ds222_ps32_s222.npy.
Files
inference_and_plot.ipynb
Files
(4.2 GB)
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md5:6174ed91ad1d7cce9f0f2a0752568cc7
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md5:56b648fabd29607a0d0ab8391b035a95
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md5:f5f9e5030b603f058bae2bb21ab89374
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1.2 GB | Download |