Japan Geoscience Union Meeting 2023

Presentation information

[E] Online Poster

S (Solid Earth Sciences ) » S-VC Volcanology

[S-VC28] International Volcanology

Tue. May 23, 2023 3:30 PM - 5:00 PM Online Poster Zoom Room (3) (Online Poster)

convener:Chris Conway(Geological Survey of Japan, AIST), Keiko Matsumoto(Geological Survey of Japan, The National Institute of Advanced Industrial Science and Technology), Taishi Yamada(Sakurajima Volcano Research Center, Disaster Prevention Research Institute, Kyoto University), Katy Jane Chamberlain(University of Liverpool)


On-site poster schedule(2023/5/24 17:15-18:45)

3:30 PM - 5:00 PM

[SVC28-P08] Shear wave velocity structure beneath San Miguel volcano, El Salvador, estimated using seismic ambient noise

Kevyn Enrique Pineda Ortiz1, *Takumi Hayashida2 (1.General Direction of Enviromental Observatory, Ministry of Enviroments and Natural Resources, El Salvador, 2.IISEE, Building Research Institute, Japan)

Keywords:San Miguel volcano, seismic ambient noise, SPAC method, seismic interferometry, phase velocity, group velocity

San Miguel volcano is one of the most active volcanos in El Salvador. However, the seismic velocity structure beneath the volcano is not entirely understood. We estimated a one-dimensional seismic velocity structure model to detect volcanic earthquakes and precisely estimate the source locations. We used seismic ambient noise data in the vertical component recorded by four broadband seismometers (three Trillium Compact and one Lennartz LE-3D/20s) from February 2014 to April 2014. We used the spatial autocorrelation (SPAC) method (Aki, 1957) and seismic interferometry technique (e.g., Wapenaar and Fokkema, 2006), assuming that the recorded ambient noise is mainly composed of Rayleigh waves. The SPAC method enabled us to estimate the phase velocity of the surface waves from 0.2 to 1.0 Hz. We derived the SPAC coefficients as functions of the distance on noise recorded for each sensor-to-sensor pair (1.5–5.5 km). Rayleigh-wave phase velocities between 0.2 and 0.4 Hz were derived from the SPAC coefficients, and phase velocities above 0.4 Hz were inferred using the zero-crossing frequencies (Ekstrom et al., 2009). We also retrieved Green’s functions with seismic interferometry, which exploits the relation between the Green’s function and the cross-correlation of ambient noise recordings. The combined use of the two methods offered ways to obtain information about near-surface to upper crustal seismic velocity structure from the same dataset. The resultant dispersion curve was obtained in a frequency band of 0.2–1.3 Hz, considering the fundamental mode phase and group velocities. Through a joint inversion of phase and group velocities (Hayashida et al., 2019), we determined a seismic velocity structure composed of four sedimentary layers with shear wave velocities in the range of 1.0–2.8 km/s overlying a half-space layer. The proposed velocity model enabled us to locate 15 volcano-tectonic earthquakes, whose location coincides with a deformation zone known as the San Miguel Zone Fault on the volcano's northern flank.

[References]
Aki, K. (1957). Space and time spectra of stationary stochastic waves, with special reference to microtremors. Bulletin of the Earthquake Research Institute, 35, 415–456.
Ekström, G., Abers, G. A., & Webb, S. C. (2009). Determination of surface-wave phase velocities across USArray from noise and Aki’s spectral formulation. Geophysical Research Letters, 36(18)
T. Hayashida, T. Yokoi, and B. Mukunda (2019), Estimation of Shallow-to-Deep Shear Wave Velocity Structure from Joint Inversion of Surface-wave Phase and Group Velocities, Journal of Japan Association for Earthquake Engineering, Vol. 19, 5_111-5_124, doi.org/10.5610/jaee.19.5_111
Wapenaar, K., & Fokkema, J. (2006). Green’s function representations for seismic interferometry. Geophysics, 71(4), SI33–SI46