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On estimating time offsets in the ambient noise correlation function caused by instrument response errors

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Broadband seismic networks are becoming more intensive, generating a large amount of data in the long-term collection process. When processing the data, the researchers rely almost on instrument response files to understand the information related to the instrument. Aiming at the process of instrument response recording and instrument response correction, we identify several sources of the instrument response phase error, including pole–zero change, the causality difference in instrument correction method, and the problem of filter coefficient recording. The data time offset range from the instrument response phase error is calculated from one sample point to several seconds using the ambient noise data recorded by multiple seismic stations. With different data delays, the time offset of the noise correlation function is estimated to be 74% to 99% of the data delay time. In addition, the influence of instrument response phase error on the measurement of seismic velocity change is analyzed by using ambient noise data with pole–zero change, and the results show that the abnormal wave velocity with exceeding the standard value is exactly in the time period of the instrument response error, which indicates that the instrument response error affects the study of seismology.
Czasopismo
Rocznik
Strony
1291--1301
Opis fizyczny
Bibliogr. 32 poz.
Twórcy
autor
  • College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130026, China
  • National Geophysical Exploration Instrument Engineering Technology Research Center, Changchun 130026, China
autor
  • College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130026, China, lin_jun@jlu.edu.cn
  • National Geophysical Exploration Instrument Engineering Technology Research Center, Changchun 130026, China
autor
  • College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130026, China
  • National Geophysical Exploration Instrument Engineering Technology Research Center, Changchun 130026, China
autor
  • College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130026, China
  • National Geophysical Exploration Instrument Engineering Technology Research Center, Changchun 130026, China
Bibliografia
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  • 3. Brenguier F, Shapiro NM, Campillo M, Ferrazzini V, Duputel Z, Coutant O, Nercessian A (2008b) Towards forecasting volcanic eruptions using seismic noise. Nat Geosci 1:126–130
  • 4. Brenguier F, Clarke D, Aoki Y, Shapiro NM, Campillo M, Ferrazzini V (2011) Monitoring volcanoes using seismic noise correlations. Comptes Rendus Geosci 343:633–638
  • 5. Campillo M, Paul A (2003) Long-range correlations in the diffuse seismic coda. Science 299:547–549. https://doi.org/10.1126/science.1078551
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  • 8. Denolle MA, Dunham EM, Prieto GA, Beroza GC (2013) Ground motion prediction of realistic earthquake sources using the ambient seismic field. J Geophys Res Solid Earth 118:2102–2118
  • 9. Denolle MA, Dunham EM, Prieto GA, Beroza GC (2014) Strong ground motion prediction using virtual earthquakes. Science 343:399–403
  • 10. Derode A, Larose E, Campillo M, Fink M (2003) How to estimate the Green’s function of a heterogeneous medium between two passive sensors? application to acoustic waves. Appl Phys Lett 83:3054–3056. https://doi.org/10.1063/1.1617373
  • 11. Durand S, Montagner JP, Roux P, Brenguier F, Nadeau RM, Ricard Y (2011) Passive monitoring of anisotropy change associated with the Parkfield 2004 earthquake. Geophys Res Lett 38:142–154
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  • 14. Hannemann K, Krüger F, Dahm T (2014) Measuring of clock drift rates and static time offsets of ocean bottom stations by means of ambient noise. Geophys J Int 196:1034–1042. https://doi.org/10.1093/gji/ggt434
  • 15. Lin FC, Ritzwoller MH, Townend J, Bannister S, Savage MK (2007) Ambient noise Rayleigh wave tomography of New Zealand. Geophys J R Astron Soc 170:649–666
  • 16. Meier U, Shapiro NM, Brenguier F (2010) Detecting seasonal variations in seismic velocities within Los Angeles basin from correlations of ambient seismic noise. Geophys J Int 181:985. https://doi.org/10.1111/j.1365-246X.2010.04550.x
  • 17. Moschetti MP, Ritzwoller MH, Shapiro NM (2007) Surface wave tomography of the western United States from ambient seismic noise: Rayleigh wave group velocity maps. Geochem Geophys Geosyst 8:Q08010. https://doi.org/10.1029/2007GC001655
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  • 22. Seats KJ, Lawrence JF, Prieto GA (2012) Improved ambient noise correlation functions using Welch’s method. Geophys J Int 188:513–523. https://doi.org/10.1111/j.1365-246X.2011.05263.x
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  • 28. Stehly L, Campillo M, Shapiro NM (2006) A study of the seismic noise from its long-range correlation properties. J Geophys Res Solid Earth 111:B10306. https://doi.org/10.1029/2005JB004237
  • 29. Stehly L, Campillo M, Shapiro NM (2007) Traveltime measurements from noise correlation: stability and detection of instrumental time-shifts. Geophys J Int 171:223–230. https://doi.org/10.1111/j.1365-246X.2007.03492.x
  • 30. Weaver RL, Lobkis OI (2001) Ultrasonics without a source: thermal fluctuation correlations at MHz frequencies. Phys Rev Lett 87:134301. https://doi.org/10.1103/PhysRevLett.87.134301
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  • 32. Xia Y, Ni S, Zeng X, Xie J, Wang B, Yuan S (2015) Synchronizing intercontinental seismic networks using the 26 s persistent localized microseismic source. Bull Seismol Soc Am 105:2101–2108. https://doi.org/10.1785/0120140252
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d6179251-779d-40ed-a295-ce96d97c6220
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