Constraining depth range of S wave velocity decrease after large earthquakes near Parkfield, California

Abstract

We use noise correlation and surface wave inversion to measure the S wave velocity changes at different depths near Parkfield, California, after the 2003 San Simeon and 2004 Parkfield earthquakes. We process continuous seismic recordings from 13 stations to obtain the noise cross‐correlation functions and measure the Rayleigh wave phase velocity changes over six frequency bands. We then invert the Rayleigh wave phase velocity changes using a series of sensitivity kernels to obtain the S wave velocity changes at different depths. Our results indicate that the S wave velocity decreases caused by the San Simeon earthquake are relatively small (~0.02%) and access depths of at least 2.3 km. The S wave velocity decreases caused by the Parkfield earthquake are larger (~0.2%), and access depths of at least 1.2 km. Our observations can be best explained by material damage and healing resulting mainly from the dynamic stress perturbations of the two large earthquakes.

Response of hydrothermal system to stress transients at Lassen Volcanic Center, California, inferred from seismic interferometry with ambient noise

“…To explore the underlying mechanism of seismic velocity changes observed, we evaluated the depth extent of changes in velocity by examining the frequency dependence of dv/v (e.g., Wu et al 2016). We recomputed NCFs with three different frequency bands (0.1-0.5 Hz, 0.3-0.7 Hz, and 0.5-0.9 Hz) that were used for the spectral whitening process and obtained the frequency-dependent dv/v time series (Fig.…”

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

“…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).…”

“…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.…”

“…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, ).…”

Slow Dynamics and Strength Recovery in Unconsolidated Granular Earth Materials: A Mechanistic Theory

“…For instance, following the M 6.0 2004 Parkfield earthquake, velocities measured on surface and borehole arrays showed a pronounced decrease in measured velocities characterized by a long recovery spanning over a decade exhibiting log time behavior (e.g., Brenguier et al, ; Li et al, ; Rubinstein & Beroza, ). The affected zone was found to depths of several kilometers (Wu et al, ). Such behavior has also been observed elsewhere such as following the 2011 M 9.0 Tohoku‐Oki earthquake on the island of Honshu (Brenguier et al, ; Minato et al, ; Nakata & Snieder, ).…”