De Matteis, Raffaella

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.

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

Ground shaking, whether it is due to natural or induced earthquakes, has always been a matter of concern since it correlates with structural/non-structural damage and can culminate in human anxiety. Industrial activities such as water injection, gas sequestration and waste fluid disposals, promote induced seismicity and consequent ground shaking that can hinder ongoing activities. Therefore, keeping in mind the importance of timely evaluation of a seismic hazard and its mitigation for societal benefits, the present study proposes specifically designed ground-motion prediction equations (GMPEs) from induced earthquakes in the St. Gallen geothermal area, Switzerland. The data analysed in this study consist of 343 earthquakes with magnitude −1.17 ≤ ML, corr ≤ 3.5 and hypocentral distance between 4 and 15 km. The proposed study is one of the first to incorporate ground motions from negative magnitude earthquakes for the development of GMPEs. The GMPEs are inferred with a two-phase approach. In the first phase, a reference model is obtained by considering the effect of source and medium properties on the ground motion. In the second phase the final model is obtained by including a site/station effect. The comparison between the GMPEs obtained in the present study with GMPEs developed for the other induced seismicity environments highlights a mismatch that is ascribed to differences in regional seismic environment and local site conditions of the respective regions. This suggests that, when dealing with induced earthquakes, GMPEs specific for the study should be inferred and used for both monitoring purposes and seismic hazard analyses.

Sub surface operations for energy production such as gas storage, fluid injection or hydraulic fracking modify the physical properties of the crust, in particular seismic velocity and anelastic attenuation. Continuously measuring these properties may be crucial to monitor the status of the reservoir. Here we propose a not usual use of the empirical ground-motion prediction equations (GMPEs) to monitor large-scale medium properties variations in a reservoir during fluid injection experiments. In practice, peak-ground velocities recorded during field operations are used to update the coefficients of a reference GMPE whose variation can be physically interpreted in terms of anelastic attenuation and seismic velocity. We apply the technique to earthquakes recorded at The Geysers geothermal field in Southern California and events occurred in the St. Gallen (Switzerland) geothermal field. Our results suggest that the GMPEs can be effectively used as a proxy for some reservoir properties variation by using induced earthquakes recorded at relatively dense networks.

We present a detailed seismic imaging of the harnessed Nesjavellir geothermal area, SW-Iceland, which is one of several geothermal fields on the flanks of the Hengill volcano. We map the vP , vS , and vPvS ratio using seismic data recorded in 2016–2020 and compare them with both a resistivity model of the same area and the rock temperature as measured in boreholes. The results show that the shallower crust (depth less than 1 km) is characterized by low vP and vS , and high vPvS ratio (around 1.9). Shallow low resistivity values at similar depths in the same area have been interpreted as the smectite clay cap of the system. At depths between 1 and 3 km the observed low vPvS ratio of 1.64–1.70 correlates with high resistivity values. In this area, characterized by temperatures larger than 240°C, the seismicity appears to be sparse and located close to the production wells. This seismicity has been interpreted as induced by the production in combination with naturally occurring earthquakes. At depths greater than 4 km, high vPvS ratio of 1.9 correlates well with low resistivity values. In the valley of Nesjavellir, a deep-seated conductive body, domes up at about 4.500 m b.sl. and coincides spatially with a significant high vPvS ratio anomaly (>1.9). Above these anomalies an elevated temperature is registered according to borehole temperature data. This is proposed here to be caused by hot 600°C–900°C cooling intrusives, close to the brittle ductile transition—probably the heat source(s) of the geothermal field above. These anomalies are at the same location as the last fissure eruption in Hengill almost 2,000 years ago. The NNE-SSW trending, deeper seismic cluster at 3–6 km depth is located at the edge of this high vPvS anomaly. The heat source of the Nesjavellir geothermal field is most likely connected to this most recent volcanism as reflected by the deep-seated low resistivity body and high vPvS ratio, located beneath the deep fault that connects the flow path of the high temperature geothermal fluid, resulting in an actively producing reservoir.

Reliable seismic hazard analyses are crucial to mitigate seismic risk. When dealing with induced seismicity the standard Probabilistic Seismic Hazard Analysis (PSHA) has to be modified because of the peculiar characteristics of the induced events. In particular, the relative shallow depths, small magnitude, a correlation with field operations, and eventually non-Poisson recurrence time. In addition to the well-known problem of estimating the maximum expected magnitude, it is important to take into account how the industrial field operations affect the temporal and spatial distribution of the earthquakes. In fact, during specific stages of the project the seismicity may be hard to be modelled as a Poisson process—as usually done in the standard PSHA—and can cluster near the well or migrate toward hazardous known or—even worse—not known faults. Here we present a technique in which we modify the standard PSHA to compute time-dependent seismic hazard. The technique allows using non-Poisson models (BPT, Weibull, gamma and ETAS) whose parameters are fitted using the seismicity record during distinct stages of the field operations. As a test case, the procedure has been implemented by using data recorded at St. Gallen deep geothermal field, Switzerland, during fluid injection. The results suggest that seismic hazard analyses, using appropriate recurrence model, ground motion predictive equations, and maximum magnitude allow the expected ground-motion to be reliably predicted in the study area. The predictions can support site managers to decide how to proceed with the project avoiding adverse consequences.

Focal mechanisms of selected earthquakes, recorded in the Mount Pollino region (southern Italy) from 2010 through 2014, are used to infer the pore fluid pressure at hypocenter depths. The 3-D excess pore pressure field provides evidence that the sequence occurs in a fluid-filled volume with values reaching 35 MPa. The mechanisms underlying this swarm-like sequence and the triggering of earthquakes are investigated by computing the cumulative static Coulomb stress change at hypocenter depths and analyzing the pore-pressure diffusion mechanism. The results indicate that static Coulomb stress change was lower than 0.01 MPa, which is the value generally assumed as threshold for the triggering, and seismicity distribution was actually driven by pore-pressure diffusion with relatively low diffusivity value. This latter mechanism could also explain the delayed triggering of the two larger events ML 4.3 and ML 5.0, respectively, that occurred about 150 days apart.

The mechanism by which faults interact each other is still a debated matter. One of the main issues is the role of pore-pressure diffusion in the delayed triggering of successive events. The 2016 Amatrice–Visso–Norcia seismic sequence (Central Apennines, Italy) provides a suitable dataset to test different physical mechanisms leading to delayed events. The sequence started on August 24, 2016, with the Amatrice mainshock (MW = 6), and was followed after more than 60 days by events in Visso (MW = 5.4) and Norcia (MW = 5.9). We analyzed the contribution of the static stress change and the role of fluids in the delayed triggering. Through 3D poroelastic modeling, we show that the Amatrice mainshock induced a pore-pressure diffusion and a normal stress reduction in the hypocentral area of the two aftershocks, favoring the rupture. Our parametric study employs a simple two-layered conductivity model with anisotropy in the seismogenic layer, characterized by larger conductivity values (K > 10􀀀5 m/s) along the NNW-SSE direction. The one-way coupled pore-pressure 3-D diffusion modeling predicts the maximum increase of the pore pressure at the location of the two Visso earthquakes 60 days after the mainshock. The occurrence of anisotropic diffusivity is supported by the pattern of active faults and the strong crustal anisotropy documented by S-wave splitting analysis. We conclude that the temporal evolution of the sequence was controlled by the anisotropic diffusion of pore-pressure perturbations through pre-existing NNW-trending fracture systems.

Sub-surface operations for energy production such as gas storage, fluid reinjection or hydraulic fracking may modify the physical properties of the rocks, in particular the seismic velocity and the anelastic attenuation. The aim of the present study is to investigate, through a synthetic test, the possibility of using empirical ground-motion prediction equations (GMPEs) to observe the variations in the reservoir. In the synthetic test, we reproduce the expected seismic activity (in terms of rate, focal mechanisms, stress drop and the b value of the Gutenberg-Richter) and the variation of medium properties in terms of the quality factor Q induced by a fluid injection experiment. In practice, peak-ground velocity data of the simulated earthquakes during the field operations are used to update the coefficients of a reference GMPE in order to test whether the coefficients are able to capture the medium properties variation. The results of the test show that the coefficients of the GMPE vary during the simulated field operations revealing their sensitivity to the variation of the anelastic attenuation. The proposed approach is suggested as a promising tool that, if confirmed by real data analysis, could be used for monitoring and interpreting induced seismicity in addition to more conventional techniques.

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.