Seismic imaging of fluid-filled inherited structures of the Northern Thessaly (Greece) seismic gap
e present the first seismic imaging of the crustal volume affected by the March April 2021 Thessaly sequence by applying a 3D seismic tomography to the aftershocks recorded by an unprecedented number of stations. The results, in terms of VP, VS, and VP/VS ratio and earthquakes’ location parameters, depict blind fluid-filled inherited structures within the Northern Thessaly seismic gap. The tomographic images highlight the basal detachment accommodating the Pelagonian nappe onto the carbonate of the Gavrovo unit. The high VP/VS (>1.85) where most of the seismicity occurs increases from SE to NW, showing possible fluid accumulation in the NW edge of the seismogenic volume that could have contributed to the sequence evolution. The aftershock relocations correlate well with the fault planes of the three mainshocks proposed by several geodetic models, but also show additional possible faults sub-parallel and antithetical to the main structures, not to be overlooked for future seismic risk mitigation
TESLA, A Tool for Automatic Earthquake Low-Frequency Spectral Level Estimation: The Study of 2013 St. Gallen Earthquake Fault-Plane Solutions
One of the challenges of seismicity monitoring is to achieve multiparametric catalogs complete down to small magnitude using automatic procedures. This can be obtained using seismic networks with high performance and robust, automatic algorithms able to process large data sets, limiting the manual operations of the analysts. The characterization of microseismicity is fundamental to study its spatial and temporal evolution and to define the seismic activity of fault systems. Among the source parameters of microseismic events, focal mechanisms are not generally calculated and, when available in the seismic catalog, their reliability may be dubious. We propose a new tool, named Tool for automatic Earthquake low‐frequency Spectral Level estimAtion (TESLA), to automatically calculate the P‐ and S‐wave low‐frequency spectral levels. Indeed, it has been shown that these levels can be inverted together with P‐phase polarities to better constrain the focal mechanism or to estimate the seismic moment. TESLA is designed to invert the P‐ and S‐displacement spectra searching the optimal signal window to use for the spectral analysis. Using a signal window of fixed duration, although variable according to the earthquake magnitude, is not always the appropriate choice, especially when microseismicity is analyzed. TESLA performs three main tasks for both P and S phases: (1) a systematic exploration of several signal windows to use for the computation of displacement spectra, (2) the spectral analysis for all the selected signal windows, and (3) the evaluation of the best‐displacement spectra through quantitative criteria and the estimation of the low‐frequency spectral levels. The tool is first validated and then applied to the 2013 St. Gallen, Switzerland, induced seismic sequence to calculate the P and S low‐frequency spectral level ratios, which are inverted to estimate focal mechanisms. Our results show the robustness of the tool to process microseismicity and the benefit of using it to automatically analyze large waveform data sets.
Seismic noise cross-correlation in the urban area of Benevento city (Southern Italy)
In the last decade the use of passive methods has become appealing in reconstructing the properties of the propagation medium by seismic ambient noise data, without the use of localized natural or artificial sources. A temporary seismic network was installed in the urban area of Benevento (southern Italy) in order to characterize the shallow structure of the city using stable methods for the analysis of the seismic noise continuously acquired by stations. The city of Benevento is one of the italian areas with highest seismic hazard, and at present the region is affected by low energy swarms and sparse events (Ml ≤ 4.1). It has been struck by several destructive historical earthquakes, the strongest of which occurred in 1456, 1688, 1805 with associated MCS intensity up to X–XI. We used the sixteen seismic stations installed in Benevento to record ambient noise for about 1 month. The stations were equipped with different seismic instruments: (i) digitizers Quanterra Q330 connected to Le3d-5 s short-period sensors; (ii) Nanometrics Centaur digitizers coupled with Trillium Compact 120s broad-band velocimeters; (iii) one station with Episensor force balance accelerometer connected to a D6BB-DIN Staneo digitizer. Interstations Green's functions were reconstructed by the cross-correlation of continuous ambient noise data, and surface waves signals were extracted from Green's Functions (GFs) for investigating the elastic properties of the subsurface structure. In this regard, we performed the beamforming analysis to test the hypothesis of isotropy distribution of noise sources on which the cross-correlation method is based, and the particle motion analysis to confirm the presence of surface Rayleigh waves in the GFs. We analysed the temporal stability of the cross-correlated signals and the results show that 2 weeks of continuous measurements are sufficient to stabilize the surface waves signal extracted from the GFs. The phase velocity dispersion curves are computed for 115 station pairs through the use of a far-field representation of the surface-wave GFs and an image transformation technique. Our strategy based on cross-correlation analysis provides robust phase-velocity dispersion curves that vary approximately from 1.4 km s–1 at 0.7 Hz to 0.6 km s–1 at 5 Hz. Different pairs were selected for the inversion of phase-velocity dispersion curves aimed to derive 1-D shear-wave velocity (Vs) profiles (up to a maximum depth of about 500 m) representative of some areas of the city characterized by different soil deposits.