Efficient seismic data denoising via multi-scale attention network with depthwise separable and residual dilated convolutions

Abstract Because a high signal-to-noise ratio (SNR) is critical in enhancing the accuracy of subsequent processing, noise reduction remains a pivotal challenge in seismic signal processing, especially for complex noise interference scenarios. To address this, we propose a novel network termed MSARDN...

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Autori principali:	Zhenjing Yao, Lei Hao, Lan Qin, Jiahao Chen, Wenzhe Li
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Nature Portfolio 2025-12-01
Serie:	Scientific Reports
Soggetti:	Seismic data Denoising Depthwise separable convolution Multi-scale attention Residual dilated convolution Deep learning
Accesso online:	https://doi.org/10.1038/s41598-025-32591-w
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