干旱区生态环境知识资源中心(Arid): Noise suppression method based on multi-scale Dilated Convolution Network in desert seismic data

Arid

DOI	10.1016/j.cageo.2021.104910
	Noise suppression method based on multi-scale Dilated Convolution Network in desert seismic data
	Li, Yue; Wang, Yuying; Wu, Ning
通讯作者	Wu, N (corresponding author), Jilin Univ, Dept Informat, Coll Commun Engn, Changchun 130012, Peoples R China.
来源期刊	COMPUTERS & GEOSCIENCES
ISSN	0098-3004
EISSN	1873-7803
出版年	2021
卷号	156
英文摘要	Seismic data denoising is an important mean to extract useful information from seismic data, remove interference, and improve the SNR(signal-to-noise ratio) of seismic data. Therefore, the research on denoising methods of seismic data has always been a hot topic. At present, most convolutional neural networks for desert seismic data denoising use single scale convolutional kernels to extract feature information, which is prone to cause missing details. Therefore, we propose the Multi-scale Dilated Convolution Network (MDCN) to remove desert seismic noise. Dilational convolution operators of different sizes are used to autocratically extract features of different scales from seismic data. The extracted features are then connected in series and fused into multi-scale information used for denoising. Moreover, using dilated convolutions can increase the receptive field, so that the output of each convolution would contain a larger range of information than single scale convolutional neural networks, which means they have access to a larger window and as a result can use temporal information. In order to increase the receiving range of the network and obtain more context information, we cascade multiple modules to form a deep network. In this way, we can extract as much detailed information as possible from the desert seismic data. The results of the experiment show that our method effectively suppresses the desert noise and also better retains the effective signal.
英文关键词	Multi-scale Dilated convolution Convolutional neural network Desert seismic data denoising
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000693187100001
WOS关键词	MODE DECOMPOSITION ; CLASSIFICATION
WOS类目	Computer Science, Interdisciplinary Applications ; Geosciences, Multidisciplinary
WOS研究方向	Computer Science ; Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/362896
作者单位	[Li, Yue; Wang, Yuying; Wu, Ning] Jilin Univ, Dept Informat, Coll Commun Engn, Changchun 130012, Peoples R China
推荐引用方式 GB/T 7714	Li, Yue,Wang, Yuying,Wu, Ning. Noise suppression method based on multi-scale Dilated Convolution Network in desert seismic data[J],2021,156.
APA	Li, Yue,Wang, Yuying,&Wu, Ning.(2021).Noise suppression method based on multi-scale Dilated Convolution Network in desert seismic data.COMPUTERS & GEOSCIENCES,156.
MLA	Li, Yue,et al."Noise suppression method based on multi-scale Dilated Convolution Network in desert seismic data".COMPUTERS & GEOSCIENCES 156(2021).