ALBERT

Description: 〈span〉〈div〉Summary〈/div〉We develop a probabilistic framework based on the conjunction of states of information between data and model, to jointly retrieve earthquake source parameters and anelastic attenuation factor from inversion of displacement amplitude spectra. The evaluation of the joint probability density functions (PDFs) enables us to take into account between-parameter correlations in the final estimates of the parameters and related uncertainties. Following this approach, we first search for the maximum of the a-posteriori PDF through the basin hopping technique that couples a global exploration built on a Markov chain with a local deterministic maximization. Then we compute statistical indicators (mean, variance and correlation coefficients) on source parameters and anelastic attenuation through integration of the PDF in the vicinity of the maximum likelihood solution. Definition of quality criteria based on the signal to noise ratio and similarity of the marginal PDFs with a Gaussian function enable us to define the frequency domain for the inversion and to get rid of unconstrained solutions.We perform synthetic tests to assess theoretical correlations as a function of the signal to noise ratio and to define the minimum bandwidth around the corner frequency for consistent parameter resolution.As an application, we finally estimate the source parameters for the 2016–2017 Central Italy seismic sequence. We found that the classical scaling between the seismic moment and the corner frequency holds, with an average stress drop of $\Delta \sigma = 2.1 \pm 0.3\,\,MPa$. However, the main events in the sequence exhibit a stress drop larger than the average value. Finally, the small seismic efficiency indicates a stress overshoot, possibly due to dynamic effects or large frictional efficiency.〈/span〉

Description: 〈span〉〈div〉SUMMARY〈/div〉We develop a probabilistic framework based on the conjunction of states of information between data and model, to jointly retrieve earthquake source parameters and anelastic attenuation factor from inversion of displacement amplitude spectra. The evaluation of the joint probability density functions (PDFs) enables us to take into account between-parameter correlations in the final estimates of the parameters and related uncertainties. Following this approach, we first search for the maximum of the 〈span〉a posteriori〈/span〉 PDF through the basin hopping technique that couples a global exploration built on a Markov chain with a local deterministic maximization. Then we compute statistical indicators (mean, variance and correlation coefficients) on source parameters and anelastic attenuation through integration of the PDF in the vicinity of the maximum likelihood solution. Definition of quality criteria based on the signal-to-noise ratio (SNR) and similarity of the marginal PDFs with a Gaussian function enable us to define the frequency domain for the inversion and to get rid of unconstrained solutions.We perform synthetic tests to assess theoretical correlations as a function of the SNR and to define the minimum bandwidth around the corner frequency for consistent parameter resolution.As an application, we finally estimate the source parameters for the 2016–2017 Central Italy seismic sequence. We found that the classical scaling between the seismic moment and the corner frequency holds, with an average stress drop of $\Delta \sigma = 2.1 \pm 0.3\,\,{\rm {MPa}}$. However, the main events in the sequence exhibit a stress drop larger than the average value. Finally, the small seismic efficiency indicates a stress overshoot, possibly due to dynamic effects or large frictional efficiency.〈/span〉

Description: We analyze two large data sets of 10 years (2009-2018) of ordinary earthquakes (OEs) detected in Italy by INGV and low-frequency earthquakes (LFEs) detected in Japan by JMA. We estimate the joint probability density function of seismic moment (M0) and corner frequency (fc) from S-wave displacement spectra. We use unfiltered signals and manually revised S-wave arrival times.We estimate a wide range of moment magnitudes (Mw = 0-6 for OEs, 0.5-2.5 for LFEs) and observe a self-similar scaling between M0 and fc for both OEs and LFEs with a constant stress-drop of ~MPa and ~kPa, respectively. However, OE spectra show a constant corner frequency fc* ~10 Hz for Mw 〈~ 2.5. We refer fc* to the cut-off frequency of the medium anelastic attenuation, acting as a low-pass filter and producing an apparent corner frequency that does not scale with the earthquake source (M0).Conversely, for the same Mw 〈~ 2.5, LFEs exhibit fc between 1 and 8 Hz that scale with M0, showing that their low-frequency content is a real source characteristic and not an apparent consequence of anelastic attenuation.Finally, both OEs (for Mw 〈~ 2.5) and LFEs show a systematic underestimation of local magnitude when compared with moment magnitude, that we analytically explain as a consequence of anelastic attenuation (fc*) for OEs and of low stress-drop (~kPa) for LFEs.Our method allows the use of raw earthquake waveforms to infer robust information both for monitoring purposes and for physical interpretations of the earthquake source in different tectonic settings and at different scales.

Description: Distributed Acoustic Sensing (DAS) is becoming a powerful tool for earthquake monitoring, providing continuous strain-rate records of seismic events along fiber optic cables. However, the use of standard seismological techniques for earthquake source characterization requires the conversion of data in ground motion quantities. In this study we provide a new formulation for far-field strain radiation emitted by a seismic rupture, which allows to directly analyze DAS data in their native physical quantity. This formulation naturally accounts for the complex directional sensitivity of the fiber to body waves and to the shallow layering beneath the cable. In this domain, we show that the spectral amplitude of the strain integral is related to the Fourier transform of the source time function, and its modeling allows to determine the source parameters. We demonstrate the validity of the technique on two case-studies, where source parameters are consistent with estimates from standard seismic instruments in magnitude range 2.0–4.3. When analyzing events from a 1-month DAS survey in Chile, moment-corner frequency distribution shows scale invariant stress drop estimates, with an average of Δσ = (0.8 ± 0.6) MPa. Analysis of DAS data acquired in the Southern Apennines shows a dominance of the local attenuation that masks the effective corner frequency of the events. After estimating the local attenuation coefficient, we were able to retrieve the corner frequencies for the largest magnitude events in the catalog. Overall, this approach shows the capability of DAS technology to depict the characteristic scales of seismic sources and the released moment.