Low‐Frequency Reconstruction for Full Waveform Inversion by Unsupervised Learning
Abstract Obtaining reliable low‐frequency seismic data is crucial for effectively reducing cycle‐skipping in full waveform inversion. However, acquiring high signal‐to‐noise ratio low‐frequency information from field data remains a challenge. An effective solution to mitigate cycle‐skipping is to ut...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2024-11-01
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| Series: | Earth and Space Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024EA003565 |
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