干旱区生态环境知识资源中心(Arid): Modeling Land Seismic Exploration Random Noise in a Weakly Heterogeneous Medium and the Application to the Training Set

Arid

DOI	10.1109/LGRS.2019.2926756
	Modeling Land Seismic Exploration Random Noise in a Weakly Heterogeneous Medium and the Application to the Training Set
	Feng, Qiankun; Li, Yue; Yang, Baojun
通讯作者	Li, Yue
来源期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN	1545-598X
EISSN	1558-0571
出版年	2020
卷号	17 期号:4 页码:701-705
英文摘要	In seismic exploration, random noise is an obstacle to the extraction of the effective signals, so the investigation aimed at random noise is the basis of signal processing. It is of great significance to analyze the noise properties and establish accurate noise models. Since the complex changes of the actual medium seriously affect propagation characteristics, it is necessary to establish a noise model in a more realistic medium. In this letter, we suppose a weakly heterogeneous medium whose properties vary with the position. And the link between the Lam constants of the medium and noise properties is established. Therefore, a wave equation is deduced in that medium to describe the propagation law of desert seismic exploration random noise. Based on the Greens function, the random noise field is obtained by superimposing all wave fields excited by each pointlike source. Afterward, quantitative comparisons between the actual random noise and the proposed random noise model are given. The results manifest that there are significant similarities in mathematical characteristics between them. Moreover, compared with the noise model in the homogeneous medium, the proposed noise model is more reliable. In order to prove the application value of the random noise model, it is first applied to construct a complete training set for denoising convolutional neural networks, which is valuable for attenuating the desert seismic exploration random noise. This is an effective way to extend noise data. Consequently, this feasible application will strongly promote the application of neural networks in seismic exploration.
英文关键词	Mathematical model Propagation Noise reduction Training Green's function methods Convolutional neural networks Denoising convolutional neural networks (DnCNN) seismic exploration random noise modeling training set wave equations in the heterogeneous medium weakly heterogeneous isotropic medium
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000522453800031
WOS关键词	SURFACE-GENERATED NOISE ; SPATIAL-CORRELATION ; DEEP ; CLASSIFICATION ; CNN
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/314711
作者单位	Jilin Univ, Dept Informat, Coll Commun Engn, Changchun 130012, Peoples R China
推荐引用方式 GB/T 7714	Feng, Qiankun,Li, Yue,Yang, Baojun. Modeling Land Seismic Exploration Random Noise in a Weakly Heterogeneous Medium and the Application to the Training Set[J],2020,17(4):701-705.
APA	Feng, Qiankun,Li, Yue,&Yang, Baojun.(2020).Modeling Land Seismic Exploration Random Noise in a Weakly Heterogeneous Medium and the Application to the Training Set.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,17(4),701-705.
MLA	Feng, Qiankun,et al."Modeling Land Seismic Exploration Random Noise in a Weakly Heterogeneous Medium and the Application to the Training Set".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 17.4(2020):701-705.