OpenFwi Pre-processed 72x72
Compressed and pre-processed version of the OpenFwi seismic dataset. Each sample is a 72×72 float16 matrix representing a simulated seismic signal for modeling or inversion tasks.
Description
OpenFwi Pre-processed 72x72 is a subset of the OpenFwi dataset, containing seismic signals transformed into square (72x72) floating point matrices. This is compressed scientific data intended for geophysical modeling, signal analysis, or reverse learning tasks. This simplified format makes it easy to use them in deep learning architectures based on convolutions.
What is this dataset for?
- Train geological structure prediction models (seismic reversal)
- Experiment with compression or dimensional reduction techniques on physical signals
- Simulate physical systems in geoscience research environments
Can it be enriched or improved?
Yes, this dataset can be enriched with geographic or physical metadata, or converted to other resolutions to test multigranular approaches. It can also be combined with geological layer annotations to add explicit supervision.
🔎 In summary
🧠 Recommended for
- Geophysicists
- Physical modeling researchers
- Signal processing engineers
🔧 Compatible tools
- NumPy
- PyTorch
- TensorFlow
- Science notebooks
💡 Tip
Convert matrices to images for quick visualization of structures or test classical CNN models
Frequently Asked Questions
Can this dataset be used with traditional image models?
Yes, 72x72 matrices can be treated as images, allowing CNNs to be used to model signals.
Does it contain annotations of geological structures?
No, it's just pre-processed seismic data. For supervised tasks, another target dataset must be integrated.
Is this reduced format suitable for production?
Yes for prototypes or rapid tests, but higher resolutions will often be required during production.
