An effective self-supervised learning method for various seismic noise attenuation

Faced with the scarcity of clean label data in real scenarios, seismic denoising methods based on supervised learning (SL) often encounter performance limitations. Specifically, when a model trained on synthetic data is directly applied to field data, its performance would drastically decline due to...

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Veröffentlicht in:	arXiv.org 2023-11
Hauptverfasser:	Cheng, Shijun, Cheng, Zhiyao, Jiang, Chao, Mao, Weijian, Zhang, Qingchen
Format:	Artikel
Sprache:	eng
Schlagworte:	Iterative methods Labels Noise prediction Noise reduction Random noise Seismic stability Self-supervised learning Synthetic data
Online-Zugang:	Volltext
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