干旱区生态环境知识资源中心(Arid): Desert seismic data denoising based on energy spectrum analysis in empirical curvelet domain

Arid

DOI	10.1007/s11200-019-0476-4
	Desert seismic data denoising based on energy spectrum analysis in empirical curvelet domain
	Li, Mo; Li, Yue; Wu, Ning; Tian, Yanan
通讯作者	Li, Y
来源期刊	STUDIA GEOPHYSICA ET GEODAETICA
ISSN	0039-3169
EISSN	1573-1626
出版年	2020
卷号	64 期号:3 页码:373-390
英文摘要	Desert seismic events are disturbed and contaminated by strong random noise, which complicates the subsequent processing, inversion, and interpretation of the data. Thus, noise suppression is an important task. The complex characteristics of random noise in desert seismic records differ completely from those of Gaussian white noise such that they are non-stationary, non-Gaussian, non-linear and low frequency. In addition, desert seismic signals and strong random noise generally share the same frequency bands. Such factors bring great difficulties in the processing and interpretation of desert seismic data. To obtain high-quality data in desert seismic exploration, we have developed an effective denoising method for desert seismic data, which performs energy spectrum analysis in the empirical curvelet transform (ECT) domain. The empirical curvelet coefficients are divided into two different groups according to their energy spectrum distributions. In the first group, which contains fewer effective signals, a large threshold is selected to remove lots of random noise; the second group, with more effective signals, a coherence-enhancing diffusion filter (CEDF) is used to eliminate the noise. Unlike traditional curvelet transforms, ECT not only has the multi-scale, multi-direction, and anisotropy properties of conventional curvelet transform, but also provides adaptability to separate the effective signals from the random noise. We examine synthetic and field desert seismic data. The denoising results demonstrate that the proposed method can be used for preserving effective signals and removing random noise.
英文关键词	empirical curvelet transform desert seismic random noise energy spectrum coherence-enhancing diffusion filtering CEDF denoising
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000549787700001
WOS关键词	RANDOM NOISE
WOS类目	Geochemistry & Geophysics
WOS研究方向	Geochemistry & Geophysics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325086
作者单位	[Li, Mo; Li, Yue; Wu, Ning; Tian, Yanan] Jilin Univ, Coll Commun & Engn, Jilin 132000, Jilin, Peoples R China
推荐引用方式 GB/T 7714	Li, Mo,Li, Yue,Wu, Ning,et al. Desert seismic data denoising based on energy spectrum analysis in empirical curvelet domain[J],2020,64(3):373-390.
APA	Li, Mo,Li, Yue,Wu, Ning,&Tian, Yanan.(2020).Desert seismic data denoising based on energy spectrum analysis in empirical curvelet domain.STUDIA GEOPHYSICA ET GEODAETICA,64(3),373-390.
MLA	Li, Mo,et al."Desert seismic data denoising based on energy spectrum analysis in empirical curvelet domain".STUDIA GEOPHYSICA ET GEODAETICA 64.3(2020):373-390.