ALBERT

Description: We investigated the shallow structure of the Solfatara, a volcano within the Campi Flegrei caldera, southern Italy, using surface waves as a diagnostic tool. We analysed data collected during the RICEN campaign, where a 3-D active seismic experiment was performed on a dense regular grid of 90 m  x  115 m using a Vibroseis as the seismic source. After removal of the source time function, we analysed the surface wave contribution to the Green's function. Here, a 1-D approximation can hold for subgrids of 40 m  x  40 m. Moreover, we stacked all of the signals in the subgrid according to source–receiver distance bins, despite the absolute location of the source and the receiver, to reduce the small-scale variability in the data. We then analysed the resulting seismic sections in narrow frequency bands between 7 and 25 Hz. We obtained phase and group velocities from a grid search, and a cost function based on the spatial coherence of both the waveforms and their envelopes. We finally jointly inverted the dispersion curves of the phase and group velocities to retrieve a 1-D S -wave model local to the subgrid. Together, the models provided a 3-D description of the S -wave model in the area. We found that the maximum penetration depth is 15 m. In the first 4 m, we can associate the changes in the S -wave field to the temperature gradient, while at greater depths, the seismic images correlate with the resistivity maps, which indicate the water layer close to the Fangaia area and an abrupt variation moving towards the northeast.

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: The use of simulated accelerograms may improve the evaluation of the seismic hazard when an accurate modelling of both source and propagation is performed. In this paper, we performed broad-band simulations of the 2009, M 6.3 L'Aquila earthquake, coupling a k –2 kinematic model for the seismic source with empirical Green's functions (EGFs) as propagators. We extracted 10 EGFs candidates from a database of aftershocks satisfying quality criteria based on signal-to-noise ratio, fault proximity, small magnitude, similar focal mechanism and stress drop. For comparison with real observations, we also derived a low-frequency kinematic model, based on inversion of ground displacement as integrated from strong motion data. Kinematic properties of the inverted model (rupture velocity, position of the rupture nucleation, low-frequency slip and roughness degree of slip heterogeneity) were used as constraints in the k –2 model, to test the use of a single specific EGF against the use of the whole set of EGFs. Comparison to real observations based on spectral and peak ground acceleration shows that the use of all available EGFs improves the fit of simulations to real data. Moreover the epistemic variability related to the selection of a specific EGF is significantly larger (two to three times) than recent observations of between event variability, that is the variability associated with the randomness of the rupture process. We finally performed ‘blind’ simulations releasing all the information on source kinematics and only considering the fault geometry and the magnitude of the target event as known features. We computed peak ground acceleration, acceleration Fourier and response spectra. Simulations follow the same trend with distance as real observations. In most cases these latter fall within one sigma from predictions. Predictions with source parameters constrained at low frequency do not perform better than ‘blind’ simulations, showing that extrapolation of the low-frequency description of the rupture front as inferred by the kinematic inversion may introduce some bias in the final simulations.

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〉