气候变化领域集成服务门户(CCPortal): Detection, Classification, and Location of Seismovolcanic Signals with Multicomponent Seismic Data: Example from the Piton de La Fournaise Volcano (La Réunion, France)

CCPortal

DOI	10.1029/2019JB019333
	Detection, Classification, and Location of Seismovolcanic Signals with Multicomponent Seismic Data: Example from the Piton de La Fournaise Volcano (La Réunion, France)
	Journeau C.; Shapiro N.M.; Seydoux L.; Soubestre J.; Ferrazzini V.; Peltier A.
发表日期	2020
ISSN	21699313
卷号	125 期号:8
英文摘要	We apply three different methods based on the analysis of the multicomponent seismic data to detect seismovolcanic tremors and other seismovolcanic signals, to propose an approach to classify them, and to locate their sources. We use continuous seismograms recorded during 1 year by 21 stations at the Piton de la Fournaise volcano (La Réunion, France). The first method allows the detection of seismovolcanic signals based on stability in time of the intercomponent cross-correlation function. Two other methods based on the simultaneous analysis of the whole network can be used to detect seismovolcanic signals and to locate their sources. In the first network-based method, the seismic wavefield is analyzed by calculating the width of the network covariance matrix eigenvalue distribution.The second network-based method consists in performing the 3-D backprojection of the interstation cross correlations in order to calculate the network response function. Simultaneous analysis of the parameters measured by the three different methods can be used to classify different types of seismovolcanic tremors. Our results demonstrate that all three methods efficiently detect seismovolcanic tremors accompanying the 2010 eruptions and the preceding pre-eruptive seismic swarms. Furthermore, Methods 2 and 3 based on simultaneous analysis of the whole network detect a large number of volcanic earthquakes. Our location results show that each seismovolcanic tremor is located in a distinct regionof the volcano, close to the eruptive site at a shallow depth, and the preceding seismic crisis is located deeper at about the sea level under the summit crater. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	cross-correlation methods; geophysics; network-based methods; Piton de la Fournaise volcano; seismovolcanic tremors; volcano seismology
语种	英语
来源期刊	Journal of Geophysical Research: Solid Earth
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/187696
作者单位	Institut des Sciences de la Terre, Université Grenoble Alpes, CNRS (UMR5275), Grenoble, France; Département de Géosciences, Ecole Normale Supérieure, PSL Res. Univ., Paris, France; Schmidt Institute of Physics of the Earth, Russian Academy of Sciences, Moscow, Russian Federation; Instituto Volcanológico de Canarias (INVOLCAN), Granadilla de Abona, Tenerife, Canary Islands, Spain; Université de Paris, Institut de Physique du Globe de Paris, CNRS, Paris, France; Observatoire Volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris, Université de Paris, CNRS (UMR 7154), La Réunion, Paris, France
推荐引用方式 GB/T 7714	Journeau C.,Shapiro N.M.,Seydoux L.,et al. Detection, Classification, and Location of Seismovolcanic Signals with Multicomponent Seismic Data: Example from the Piton de La Fournaise Volcano (La Réunion, France)[J],2020,125(8).
APA	Journeau C.,Shapiro N.M.,Seydoux L.,Soubestre J.,Ferrazzini V.,&Peltier A..(2020).Detection, Classification, and Location of Seismovolcanic Signals with Multicomponent Seismic Data: Example from the Piton de La Fournaise Volcano (La Réunion, France).Journal of Geophysical Research: Solid Earth,125(8).
MLA	Journeau C.,et al."Detection, Classification, and Location of Seismovolcanic Signals with Multicomponent Seismic Data: Example from the Piton de La Fournaise Volcano (La Réunion, France)".Journal of Geophysical Research: Solid Earth 125.8(2020).