association-rosia/segmenting-subsurface
Deep Learning solution for multi-layer seismic data segmentation using Meta's SAM, trained on a dataset of 9,000 volumes for improved subsurface mapping.
This project helps geophysicists and seismic interpreters efficiently map subsurface geological layers. It takes 3D seismic volume data and automatically identifies and segments multiple geological layers. This streamlines the interpretation process, providing clear, segmented outputs for further analysis, saving significant manual effort for geoscientists.
No commits in the last 6 months.
Use this if you need to rapidly and accurately identify and segment multiple geological layers within large 3D seismic datasets.
Not ideal if your primary need is for surface-level image segmentation or if you don't work with 3D seismic volume data.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Apr 23, 2024
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