Passive monitoring of anisotropy change associated with the Parkfield 2004 earthquake

Durand, S.; Montagner, Jean‐Paul; Roux, Philippe; Brenguier, Florent; Nadeau, R. M.; Ricard, Yanick

doi:10.1029/2011gl047875

Cited by 38 publications

(54 citation statements)

References 22 publications

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“…By analyzing auto‐correlation functions in the source area, Ohmi et al [2008]found seismic velocity changes caused by the 2007 Noto Hanto Earthquake. Using ambient seismic noise cross‐correlations of the Parkfield event, Brenguier et al [2008a] observed a coseismic velocity decrease of 0.08% and a postseismic recovery process and Durand et al [2010] found an anisotropy change caused by the same earthquake. Chen et al [2010]analyzed wave velocity variations associated with the 2008 Wenchuan Earthquake by ambient noise cross‐correlations.…”

Section: Introductionmentioning

confidence: 99%

Coseismic and postseismic elastic wave velocity variations caused by the 2008 Iwate‐Miyagi Nairiku earthquake, Japan

Hobiger¹,

Wegler²,

Shiomi³

et al. 2012

J. Geophys. Res.

109

104

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[1] We analyze coseismic and postseismic velocity variations caused by the June 13, 2008 Iwate-Miyagi Nairiku earthquake (M W = 6.9) using Passive Image Interferometry (PII). Seismic noise is correlated in order to reconstruct the Green's function between two sensors. Shear wave velocity changes are determined by relating the coda parts of the daily Green's functions to a long-term reference Green's function. Our study extends from January 2008 to August 2010 and includes the correlations for 190 station pairs in three different frequency ranges from 0.125 to 1.0 Hz. We show that combining the 9 different component cross-correlation functions stabilizes the velocity change estimation and increases analysis resolution. The observed velocity change curves can be fitted by model time series consisting of a coseismic velocity drop followed by logarithmic postseismic recovery and seasonal velocity variations. The coseismic velocity drops are stronger at higher frequencies and are concentrated in the southern part of the fault zone. A tomography algorithm was developed to reproject the observed velocity variations of the different sensor pairs onto the single sensors. The depth distribution of coseismic changes was modeled for the three stations with the largest velocity drops. At two stations, the coseismic velocity changes are located in the upper several hundred meters. The third station shows indications for deeper changes, in the order of kilometers. Postseismic recovery takes significantly longer than the analyzed two year period. Seasonal velocity variations with periods of one year are observed at all analyzed frequencies for most station pairs.

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Section: Introductionmentioning

confidence: 99%

Coseismic and postseismic elastic wave velocity variations caused by the 2008 Iwate‐Miyagi Nairiku earthquake, Japan

Hobiger¹,

Wegler²,

Shiomi³

et al. 2012

J. Geophys. Res.

109

104

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“…[, ]; Brenguier et al . [])), variations in crustal scattering [ Audet , ], and variations in the polarization of surface waves [ Durand et al ., ], as well as studies of GPS and InSAR data (e.g., Johanson et al . []; Johnson et al ., ; Freed , []).…”

Section: Introductionmentioning

confidence: 99%

Temporal changes in attenuation associated with the 2004 M6.0 Parkfield earthquake

et al. 2013

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Elevated seismic attenuation is often observed in fault zones due to the high degree of fracturing and fluid content. However, temporal changes in attenuation at the time of an earthquake are poorly constrained but can give indications of fracture damage and healing. In this study, spectral ratios between earthquakes within repeating clusters are calculated in an attempt to resolve temporal variations in attenuation at the time of the 2004 M6.0 Parkfield earthquake. A sharp increase in attenuation is observed immediately after the earthquake, which then decays over the next 2 years. Influences of intercluster magnitude variations, time window length and previously reported postseismic velocity changes are investigated. The postseismic decay is fit by a logarithmic function. The timescale of the decay is found to be similar to that in GPS data and ambient seismic noise velocities following the 2004 M6.0 Parkfield earthquake. The amplitude of the attenuation change corresponds to a decrease of approximately 10% in Qp at the time of the earthquake. The greatest changes are recorded on the northeast of the fault trace, consistent with preferential damage in the extensional quadrant behind a north‐westerly propagating rupture tip. Our analysis suggests that significant changes in seismic attenuation and hence fracture dilatancy during coseismic rupture are limited to depths of less than about 5 km.

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“…Even so, several authors have presented the full matrix of possible time‐domain ambient noise correlations from three‐component instruments (Campillo & Paul 2003; Stehly et al. 2007; Roux 2009; Durand et al. 2011; Roux et al.…”

Section: Introductionmentioning

confidence: 99%

Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves

Haney

Mikesell

Wijk

et al. 2012

Geophysical Journal International

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SUMMARY Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three‐component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non‐zero off‐diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out‐of‐plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed‐component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time‐domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.

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Passive monitoring of anisotropy change associated with the Parkfield 2004 earthquake

Cited by 38 publications

References 22 publications

Coseismic and postseismic elastic wave velocity variations caused by the 2008 Iwate‐Miyagi Nairiku earthquake, Japan

Coseismic and postseismic elastic wave velocity variations caused by the 2008 Iwate‐Miyagi Nairiku earthquake, Japan

Temporal changes in attenuation associated with the 2004 M6.0 Parkfield earthquake

Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves

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