Coseismic and post-seismic velocity changes detected by Passive Image Interferometry: comparison of one great and five strong earthquakes in Japan

Hobiger, Manuel; Wegler, Ulrich; Shiomi, Katsuhiko; Nakahara, Hisashi

doi:10.1093/gji/ggw066

Cited by 59 publications

(67 citation statements)

References 70 publications

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“…Several studies investigated the coseismic response of the shallow subsurface during the 2011 Tohoku‐Oki event using seismic interferometry between surface and deep‐borehole data (Nakahara, ; Nakata & Snieder, ; Sawazaki & Snieder, ; Takagi et al, ) and found relative velocity drops ranging between 5% and 22% in northeastern Japan. Autocorrelation of continuous signals recorded in deep boreholes (Minato et al, ; Hobiger et al, ) showed lower velocity drops, with maximum values of 2% during the mainshock. All these studies concluded that the velocity drops were generated by ground motion‐induced damage, with a decreasing effect with increasing depths.…”

Section: Coseismic and Postseismic Response Of The Near Surface In Grmentioning

confidence: 99%

“…Without necessarily interpreting the phases in the cross correlograms, one can also monitor the temporal evolution of the wave arrival times. AC and SC functions have been used to detect seismic velocity changes during earthquakes (Gassenmeier et al, 2016;Hobiger et al, 2012Hobiger et al, , 2014Hobiger et al, , 2016Richter et al, 2014;Wegler & Sens-Schönfelder, 2007) and volcanic eruptions (De Plaen et al, 2016). However, these studies focused on velocity changes of coda waves at relatively low frequencies (∼0.1 to 4 Hz), making the measurements sensitive to variations occurring within a few kilometers of depth.…”

Section: 1029/2018jb015697mentioning

confidence: 99%

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Complex Near‐Surface Rheology Inferred From the Response of Greater Tokyo to Strong Ground Motions

et al. 2018

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Strong ground motion can induce dynamic strains large enough for the Earth's subsurface to respond nonlinearly and to cause permanent, or plastic, damage. The 2011 Mw 9.0 Tohoku‐Oki earthquake, Japan, generated exceptional and well‐recorded ground motions in the greater Tokyo area. We use continuous records from 234 stations of the dense MeSO‐net seismic network to monitor the temporal evolution of the material properties of the shallow subsurface (upper ∼100 m). We apply the single‐station cross‐correlation method to reconstruct the near‐surface reflectivity response through time. We find that the strong ground motions from the mainshock caused large perturbations in the near‐surface structure, with significant drops in seismic velocities up to 11%. For most sites, we observe a logarithmic and complete recovery of the seismic wave speed, suggesting a relaxation process that can be explained by a viscoelastic rheology. Some sites exhibit an instantaneous and permanent change, which suggests a plastic rheology. Finally, dense seismic measurements allow for statistical inference between seismic velocity drops, recovery time scales, and permanent perturbations and ground motion strength and site conditions. This study highlights the potential for seismic interferometry to assess near‐surface rheology with dense seismic arrays.

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Section: Coseismic and Postseismic Response Of The Near Surface In Grmentioning

confidence: 99%

Section: 1029/2018jb015697mentioning

confidence: 99%

Complex Near‐Surface Rheology Inferred From the Response of Greater Tokyo to Strong Ground Motions

et al. 2018

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“…Generally, the coda wave, especially the early part of coda that has been used to investigate the seismic velocity variations in the underground medium through ambient noise technique, can be viewed as primarily dominated by surface wave energy (Obermann et al, 2013(Obermann et al, , 2016. Therefore, we can analyze the seismic velocity variations at different depths through measuring the seismic velocity variations in different period (or frequency) bands (e.g., Hobiger et al, 2016;Liu et al, 2014;Nimiya et al, 2017;Taira et al, 2018;Wu et al, 2016).…”

Section: 1029/2018jb015986mentioning

confidence: 99%

“…In the past, most noise-based monitoring studies mainly focused on the changes in coseismic velocities (e.g., Chen et al, 2010;Takagi et al, 2012;Wegler et al, 2009;Wegler & Sens-Schönfelder, 2007;Yu & Hung, 2012;Zaccarelli et al, 2011). In recent years, we have seen a rapid increase in studies on the postseismic velocity changes or recovery of seismic velocity as a result of high-quality and long-term seismic observation (e.g., Gassenmeier et al, 2016;Hobiger et al, 2012Hobiger et al, , 2016Liu et al, 2014;Soldati et al, 2015;Taira et al, 2018;Ueno et al, 2012;Wu et al, 2016). Hobiger et al (2016) systematically studied the characteristics of seismic velocity recovery in different frequency bands of different earthquakes and found that the recovery time constant for all earthquakes was 0.55 years, wherein the coseismic velocity reduction is further divided into two sections: one is potential maximal recovery value, and the other is nonrecovery residual value, and the recovery time constant is defined as the time when the coseismic velocity drop recovers to a factor of 1/e of the maximal recovery value using an exponential fitting algorithm.…”

Section: Slow Postseismic Recovery: Slow Healing?mentioning

confidence: 99%

“…In the past decade, the technique employing the reconstructed Green's function with similar waveforms from seismic ambient noise correlation to monitor the change in seismic velocity has been rapidly developing. A large number of studies have used this technique to detect temporal changes in the crust, including seasonal variations (e.g., Sens‐Schönfelder & Wegler, ; Wang et al, ), velocity changes related to the volcanic eruptions (e.g., Brenguier, Shapiro, et al, ), and the occurrence of strong earthquakes (e.g., Brenguier, Campillo, et al, ; Chen et al, ; Hobiger et al, , ; Liu et al, ; Nimiya et al, ; Soldati et al, ; Takagi et al, ; Taira et al, ; Wegler & Sens‐Schönfelder, ; Wegler et al, ; Wu et al, ; Yu & Hung, ; Zaccarelli et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Ambient Noise Monitoring of Seismic Velocity Around the Longmenshan Fault Zone From 10 Years of Continuous Observation

Liu

Huang

et al. 2018

JGR Solid Earth

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We present 10‐year continuous seismic velocity changes from 2007 to 2017 around the Longmenshan fault zone, where the 2008 Mw 7.9 Wenchuan earthquake and the 2013 Mw 6.6 Lushan earthquake occurred. We collected continuous waveforms recorded by 20 broadband stations covering the entire Longmenshan fault zone and used three‐component ambient noise correlation techniques to measure the velocity changes in four different period bands. Our results show that a significant drop, 0.04–0.06%, occurred in the coseismic velocity at the time of the Wenchuan earthquake, near the rupture zone for the period bands of 1–3 and 3–8 s. In addition, only one fourth of the coseismic velocity drop has been recovered 9 years after the earthquake. We also observed a subtle velocity drop, 0.0066%, delayed by ~100 days relative to the time of the mainshock in the period bands of 6–15 s. In the source region of the Lushan earthquake, we detected a weak but reliable coseismic velocity change of ~0.01% in the period band of 1–3 s. The physical mechanism of the seismic velocity change could involve the damage in the shallow subsurface layer (<3 km), the damage in the fault zone at depth (~10 km), and the postseismic slip along the deep rupture zone up to ~20 km. The uncommonly slow postseismic velocity recovery indicates the slow healing of the Longmenshan fault zone after the Wenchuan earthquake, which may be associated with the low rate of stress loading onto the fault zone.

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S-coda and Rayleigh waves from a decade of repeating earthquakes reveal discordant temporal velocity changes since the 2004 Sumatra Earthquake

Lin²,

et al. 2020

Preprint

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Temporal changes in the subsurface seismic velocity structure reflect the physical processes that modulate the properties of the media through which seismic waves propagate. These processes, such as healing of the surface damage zone and deep crustal deformation, are described by similar functional forms and operate on similar timescales, making it difficult to determine which process drives the observed changes. We examine earthquake-induced velocity changes using the measured lag-time time series τ(t) of the repeating earthquake sequences since the 2004 M w 9.2 Sumatra and 2005 M w 8.6 Nias earthquakes. The S coda velocity changes (δV S , equivalent to −τ S ) recover steadily during the 2005-2015 period. The Rayleigh wave velocity changes (δV LR , or −τ LR ) undergo transient recovery, followed by a strong δV LR reduction in late 2007. δV S recovery is most likely driven by deep processes, whereas the temporal breaks in δV LR recovery in 2007 mostly reflect surface damage and healing induced by the strong ground

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Coseismic and post-seismic velocity changes detected by Passive Image Interferometry: comparison of one great and five strong earthquakes in Japan

Cited by 59 publications

References 70 publications

Complex Near‐Surface Rheology Inferred From the Response of Greater Tokyo to Strong Ground Motions

Complex Near‐Surface Rheology Inferred From the Response of Greater Tokyo to Strong Ground Motions

Ambient Noise Monitoring of Seismic Velocity Around the Longmenshan Fault Zone From 10 Years of Continuous Observation

S-coda and Rayleigh waves from a decade of repeating earthquakes reveal discordant temporal velocity changes since the 2004 Sumatra Earthquake

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