干旱区生态环境知识资源中心(Arid): Desert seismic random noise reduction framework based on improved PSO-SVM

Arid

DOI	10.1007/s40328-019-00283-3
	Desert seismic random noise reduction framework based on improved PSO-SVM
	Li, Mo; Li, Yue; Wu, Ning; Tian, Yanan; Wang, Teng
通讯作者	Li, Yue
来源期刊	ACTA GEODAETICA ET GEOPHYSICA
ISSN	2213-5812
EISSN	2213-5820
出版年	2020
卷号	55 期号:1 页码:101-117
英文摘要	As one of the major regions of carbonate rock oil-gas exploration in western China, Tazhong area of the Tarim Basin has severe environment and complex ground surface conditions, hence the signal to noise ratio (SNR) of the field seismic data is extremely low. To improve the SNR of desert seismic data is a crucial step in the following work. However, the random noise in desert seismic characterizes by non-stationary, non-gaussian, non-linear and low frequency, which are very different from the random Gaussian noise. In addition, the effective signals of desert seismic generally share the same frequency band with strong random noise. These all make some traditional denoising methods cannot suppress it well. Therefore, a new noise suppression framework based on improved PSO-SVM is proposed in this paper. First, we extract the correlation of noisy desert seismic data to form feature vector. Subsequently, the model of improved PSO-SVM was built to classify the extracted feature, thereby identifying the position of the seismic events. Finally, second-order TGV filter was applied for obtaining denoised results. We perform tests on synthetic and field desert seismic record and the denoising results show that the proposed method can effectively preserve effective signals and eliminate random noise.
英文关键词	Desert random noise attenuation Correlation Particle swarm optimization (PSO) Support vector machine (SVM) Second order total generalized variation (Second-order TGV)
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000512814200007
WOS关键词	CLASSIFICATION
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/2XILL650/313881
作者单位	Jilin Univ, Coll Commun & Engn, Changchun 130012, Jilin, Peoples R China
推荐引用方式 GB/T 7714	Li, Mo,Li, Yue,Wu, Ning,et al. Desert seismic random noise reduction framework based on improved PSO-SVM[J],2020,55(1):101-117.
APA	Li, Mo,Li, Yue,Wu, Ning,Tian, Yanan,&Wang, Teng.(2020).Desert seismic random noise reduction framework based on improved PSO-SVM.ACTA GEODAETICA ET GEOPHYSICA,55(1),101-117.
MLA	Li, Mo,et al."Desert seismic random noise reduction framework based on improved PSO-SVM".ACTA GEODAETICA ET GEOPHYSICA 55.1(2020):101-117.