Monitoring of velocity changes based on seismic ambient noise: A brief review and perspective

作     者：Qing-Yu Wang HuaJian Yao Qing-Yu Wang;HuaJian Yao

作者机构：University Grenoble AlpesCNRSISTerreGrenobleFrance Laboratory of Seismology and Physics of Earth’s InteriorSchool of Earth and Space SciencesUniversity of Science and Technology of ChinaHefei 230026China Chinese Academy of Sciences Center for Excellence in Comparative PlanetologyUniversity of Science and Technology of ChinaHefei 230026China Mengcheng National Geophysical ObservatoryUniversity of Science and Technology of ChinaMengcheng Anhui 233500China 

出 版 物：《Earth and Planetary Physics》 (地球与行星物理（英文版）)

年 卷 期：2020年第4卷第5期

页      面：532-542页

核心收录：

学科分类：081801[工学-矿产普查与勘探] 081802[工学-地球探测与信息技术] 08[工学] 0818[工学-地质资源与地质工程] 

基　　金：This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(grant no.XDB 41000000) the China Seismic Experiment Site,China Earthquake Administration(project code 2018CSES0101) 

主　　题：ambient noise correlation noise-based monitoring seismic wave velocity changes the evolution of physical properties of the crust 

摘      要：Over the past two decades,the development of the ambient noise cross-correlation technology has spawned the exploration of underground *** addition,ambient noise-based monitoring has emerged because of the feasibility of reconstructing the continuous Green’s *** the physical properties of a subsurface medium by tracking changes in seismic wave velocity that do not depend on the occurrence of earthquakes or the continuity of artificial sources dramatically increases the possibility of researching the evolution of crustal *** this article,we outline some state-of-the-art techniques for noise-based monitoring,including moving-window cross-spectral analysis,the stretching method,dynamic time wrapping,wavelet cross-spectrum analysis,and a combination of these measurement methods,with either a Bayesian least-squares inversion or the Bayesian Markov chain Monte Carlo *** briefly state the principles underlying the different methods and their pros and *** elaborating on some typical noisebased monitoring applications,we show how this technique can be widely applied in different scenarios and adapted to multiples *** list classical applications,such as following earthquake-related co-and postseismic velocity changes,forecasting volcanic eruptions,and tracking external environmental forcing-generated transient *** monitoring cases having different targets at different scales,we point out the applicability of this technology for disaster prediction and early warning of small-scale reservoirs,landslides,and so ***,we conclude with some possible developments of noise-based monitoring at present and summarize some prospective research *** improve the temporal and spatial resolution of passive-source noise monitoring,we propose integrating different methods and seismic *** interdisciplinary collaboration is indispensable for comprehensively interpreting the observed changes.