Deblending of seismic data in the wavelet domain via a convolutional neural network based on data augmentation

Blended acquisition, which allows multiple sources almost simultaneously fired, has become an effective way for accelerating seismic data acquisition. In order to use conventional processing methods for imaging, deblending is necessary for this special acquisition. Convolutional neural network‐based...

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Veröffentlicht in:	Geophysical Prospecting 2024-01, Vol.72 (1), p.213-228
Hauptverfasser:	Wang, Shaowen, Song, Peng, Tan, Jun, Xia, Dongming, Du, Guoning, Wang, Qianqian
Format:	Artikel
Sprache:	eng
Schlagworte:	Acceleration Artificial neural networks Computation Data acquisition Data augmentation Datasets deblending Discrete Wavelet Transform neural network Neural networks Seismic data Synthetic data Wavelet transforms
Online-Zugang:	Volltext
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