干旱区生态环境知识资源中心(Arid): Use of the shearlet energy entropy and of the support vector machine classifier to process weak microseismic and desert seismic signals

Arid

DOI	10.5802/crgeos.3
	Use of the shearlet energy entropy and of the support vector machine classifier to process weak microseismic and desert seismic signals
	Li, Yue; Fan, Shiyu; Zhang, Chao; Yang, Baojun
通讯作者	Zhang, C
来源期刊	COMPTES RENDUS GEOSCIENCE
ISSN	1631-0713
EISSN	1778-7025
出版年	2020
卷号	352 期号:1 页码:103-113
英文摘要	Low-amplitude signal detection is a key procedure in borehole microseismic and desert seismic exploration. Usually, signals are difficult to detect due to their low amplitude and noise contamination. To solve this problem, we propose a method combining shearlet energy entropy with a support vector machine (SVM) to detect low-amplitude signals. In the proposed method, the signal feature is extracted using shearlet energy entropy. The signal is more sparsely represented in the shearlet domain because of the multi-scale and multi-direction characteristic of the shearlet transform, which favours signal feature extraction. Furthermore, in calculating shearlet energy entropy, we use the correlation of shearlet coefficients to enhance the difference between signal and noise in the shearlet domain. Shearlet energy entropy makes the SVM achieve a more accurate classification result compared with other traditional features such as amplitude and energy. The results of synthetic and field data show that our method is more effective than the STA/LTA and the convolutional neural network for low-amplitude microseismic signal and desert seismic signal detection.
英文关键词	Shearlet energy entropy SVM Microseismic signal Desert seismic signal Signal detection
类型	Article
语种	英语
开放获取类型	Bronze
收录类别	SCI-E
WOS记录号	WOS:000573960500008
WOS关键词	RANDOM NOISE ; TRANSFORM ; PICKING
WOS类目	Geosciences, Multidisciplinary
WOS研究方向	Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326578
作者单位	[Li, Yue; Fan, Shiyu; Zhang, Chao] Jilin Univ, Coll Commun Engn, Dept Informat, Changchun, Jilin, Peoples R China; [Yang, Baojun] Jilin Univ, Dept Geophys, Changchun, Jilin, Peoples R China
推荐引用方式 GB/T 7714	Li, Yue,Fan, Shiyu,Zhang, Chao,et al. Use of the shearlet energy entropy and of the support vector machine classifier to process weak microseismic and desert seismic signals[J],2020,352(1):103-113.
APA	Li, Yue,Fan, Shiyu,Zhang, Chao,&Yang, Baojun.(2020).Use of the shearlet energy entropy and of the support vector machine classifier to process weak microseismic and desert seismic signals.COMPTES RENDUS GEOSCIENCE,352(1),103-113.
MLA	Li, Yue,et al."Use of the shearlet energy entropy and of the support vector machine classifier to process weak microseismic and desert seismic signals".COMPTES RENDUS GEOSCIENCE 352.1(2020):103-113.