ovcharenkoo/mtl_low
Multi-task learning for low-frequency extrapolation and elastic model building
This project helps geophysicists improve the quality of their seismic surveys. It takes high-frequency seismic data and extrapolates the missing low-frequency components, while simultaneously building a more accurate subsurface elastic model. This results in clearer images of the Earth's interior, particularly useful for tasks like oil and gas exploration or underground structural analysis.
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Use this if you are a geophysicist or seismic interpreter looking to enhance the accuracy of your full-waveform inversions by addressing the common challenge of missing low-frequency seismic data and needing a reliable initial subsurface model.
Not ideal if you primarily work with field data and require direct application without access to synthetic data generation tools or advanced computational setups for deep learning and full-waveform inversion.
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Jun 27, 2022
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