Shear Velocity Inversion Using Multimodal Dispersion Curves From Ambient Seismic Noise Data of USArray Transportable Array

Abstract

We utilize an array method called the frequency‐Bessel transformation method to extract the multimodal dispersion curves of Rayleigh waves from ambient seismic noise data recorded by the USArray Transportable Array. We observe as many as five overtones' dispersion curves of Rayleigh waves in the Midwestern United States, and four and three overtones' dispersion curves, respectively, in the U.S. Great Plain area and Northeastern United States. We employ a quasi‐Newton method to invert the multimodal dispersion curves for the shear velocity. We find that the sensitivity of overtones to deeper structures is higher than that of fundamental mode in the same frequency range. The utilization of overtones significantly improved the non‐uniqueness and convergence of the inversions, which make the final inversion results robust and reliable. Our inversion results for S wave velocity (Vs) model in the studied areas exhibit some differences compared with Shen and Ritzwoller's model (2016, https://doi.org/10.1002/2016JB012887). The Vs falls abruptly in the lower crust (21–33 km) in the U.S. Great Plain area and Northeastern U.S. areas. A high‐velocity zone is observable in depth of 50–60 km in the U.S. Great Plain area and Midwestern United States, and all three models show larger Vs values below 50 km than those of Shen and Ritzwoller (2016).

The Frequency‐Bessel Spectrograms of Multicomponent Cross‐Correlation Functions From Seismic Ambient Noise

“…However, although the F‐J method has been successfully applied to active and passive source data to extract multimode surface wave dispersion curves (Li & Chen, 2020; Wang et al., 2019; Wu et al., 2019; Yang et al., 2019), it currently can only deal with ZZ component CCFs. On the one hand, other‐component CCFs provide complementary information of the Earth's structure (Aki, 1957; Gribler & Mikesell, 2019; Haney et al., 2012; Xia, 2014).…”

Refining Higher Modes of Rayleigh Waves Using Seismoelectric Signals Excited by a Weight‐Drop Source: Study From Numerical Simulation Aspect

“…The F‐J method is very effective in extracting multimodal dispersion information of surface waves from array seismic records. In previous works (Li & Chen, 2020; Wang et al., 2019; Wu et al., 2020), the F‐J method is introduced and applied for the vertical seismic component only. In this study, we extend the F‐J method to account for the concerned seismic and electric components (i.e., u r , u z, and E r ).…”

“…The surface wave method, such as Rayleigh wave method or Love wave method, is an appealing noninvasive tool for estimating the subsurface shear wave velocity structures from seismic recordings generated by active source, passive source, or natural earthquake (e.g., Bensen et al., 2007; Li et al., 2019; Nakata et al., 2011; Shapiro et al., 2005; Shen & Ritzwoller, 2016; Xia et al., 1999). It has been widely applied in various fields, such as near‐surface geophysical exploration (e.g., Beaty et al., 2002; Cheng et al., 2016; Dal Moro et al., 2019; Foti et al., 2011; Park et al., 1999), and regional or global seismology (e.g., Lin et al., 2008; Wu et al., 2020; Yang et al., 2007; Yao et al., 2006). This method is based on the dispersion characteristic of surface waves, and can be divided into three main procedures: field data acquisition, dispersion curve extraction, and dispersion curve inversion (e.g., Park et al., 1999; Socco et al., 2010).…”

“…Recently, Wang et al (2019) introduced an array-based method named the frequency-Bessel transform method (abbreviated as the F-J method), which shows a powerful ability to extract the higher modes of Rayleigh waves from ambient seismic noise data. Using the F-J method, Wu et al (2020) extracted the multimodal dispersion curves from ambient seismic noise data of USArray/Transportable Array, and demonstrated the important role of the higher modes in the shear-wave velocity inversion. Inspired by the success of the application of the F-J method to ambient seismic noise data, Li and Chen (2020) extended the F-J method to extract the overtones (i.e., higher modes) of surface waves from array seismic records of earthquake events.…”

An Effective Method to Extract Overtones of Surface Wave From Array Seismic Records of Earthquake Events

“…Transportable Array (TA) have shown that the F-J method is very robust and efficient. Based on the overtones extracted by the F-J method, Wu et al (2020) demonstrated that overtones can significantly improve the nonuniqueness and convergence of the shear-wave velocity inversion.…”