Search

To determine the crustal rock rheological properties and model wave propagation in an anelastic attenuating medium, it is necessary to determine the quality factor Q, which expresses the fraction of friction-dissipated energy to total seismic energy. Measuring time-broadening of the first P- and S-wave pulses, we propose a time-domain method to estimate the frequency-independent Q parameter of body waved from microearthquake records. We assume a uniform velocity, circular rupture model as represented by a triangular moment rate/displacement function, whose attenuated velocity pulse widths are analyzed in the near-source distance range. The attenuated velocity pulse width data allow the calculation of the source parameters, including rupture duration/radius and stress drop values, as well as the attenuation factor t* (travel distance/quality factor), used to determine the attenuation structure in the study area. It is noted that the constant coefficient of the pulse-width vs t* relationship, required for calculating the t* catalog, have been calibrated for a triangular displacement waveform through simulation analysis. An evaluation of the methodology was carried out on 126 micro-events with Mw ranging from 1 to 3 located around the PRATI-9 and PRATI-29 injection wells at the Geyser geothermal field, California. The analysis of the P- and S-waves indicates a Qp range of 55 to 100 and a Qs range of 89 to 189. To validate the the t* data, we have inverted them to obtain a 1D QP model that matches consistently with the profiles derived from existing tomographic QP models in the area.

The rupture process of the recent moderate-to-large earthquakes in the longest seismic sector in Iran's plateau, the Zagros area, has been modeled using the strong motion data provided by the Iranian Building and Housing Research Center (BHRC). The selected dataset includes the largest and deadliest seismic event, the 2017 Mw 7.3, Sarpol-e Zahab earthquake. The earthquake source parameters (moment magnitude, source duration, rupture dimension, and average stress drop) are determined by implementing a parametric modeling technique in the time domain based on the time evolution of the P-wave displacement signals. The seismic source parameters are calculated from simulated trapezoidal and triangular moment-rate functions assuming the unilateral rectangle and circular crack models, respectively, where the rupture propagates at a constant velocity as a fraction (90%) of the average shear-wave velocity in the medium. The anelastic attenuation effect assuming the independent frequency-Q parameter ranging from 50 to 200 is accounted for by a post-processing procedure that retrieved the observed moment-rate triangular shape. Hence, the average stress drop with different varies between =1.50 (1.14−1.95) and =0.90 (0.71−1.14) MPa. Assuming a circular rupture model for Sarpol-e-Zahab, we estimate a moment magnitude of 7, rupture duration of 7 seconds, source radius of 16 km, and statistical stress drop of about 3.5 MPa. Alternatively, a unilateral rupture model calculates the fault length and width at 45 and 16 km, with a lower stress drop of 2 MPa.

Non-linear response of the elastic properties of the crust has been studied using the analysis of seismic velocity variations induced by various natural forcing agents (earthquakes, tides, volcanic processes, and others). Here we study 1) the variations of seismic velocities in response non-tectonic deformations associated to phases of groundwater recharge/discharge in large karstic aquifers in the Southern Apennines of Italy and discuss 2) the implications in terms of non-elastic behavior of the crust. Karst systems are complex aquifers common within the carbonate rocks of the Apennines. They store large amount of groundwater producing significant horizontal dilatational strains that modulate the secular, tectonic deformation (~3 mm/yr extension across the Apennines) and background seismicity (Silverii et al., 2019; D’Agostino et al., 2018) with seasonal and multi-seasonal signatures. The availability of accurate and temporally-long hydrological measurements (rainfall and karst spring discharge) in addition to dense seismic and geodetic networks provide the opportunity to assess the elastic response of the crust to strain forcing at various periods and the sensitivity of relative velocity variations to non-tectonic, hydrological strain variations. We performed velocity variation measurements on seismic noise autocorrelation signals recorded at seismic stations for different coda waves time lapse and compared them with strain measured by the GPS network. We observe that seismic velocities decrease during dilatation episodes (high hydraulic head) and increase during contraction (low hydraulic head). We find that the retrieved strain sensitivity of seismic velocity changes is of the order of ~103 and discuss such sensitivity with previous natural and laboratory results.

Water injection in geothermal areas is the preferential strategy to sustain the natural production of geothermal resources. In this context, monitoring microearthquakes is a fundamental tool to track changes in the reservoirs in terms of soil composition, response to injections, and resource exploitation in space and time. Therefore, the refined source characterization is crucial to better estimate the size, source mechanism, and rupture process of microearthquakes, as possibly related to industrial activities and to identify any potential variation of the background seismicity. Standard approaches for source parameters estimation are ordinarily based on the modelling of Fourier displacement spectra and its characteristic parameters, the low-frequency spectral level and corner frequency. Here we apply a time-domain innovative technique that uses the curves of P-wave amplitude vs time along the seismogram. The methodology allows estimating seismic moment, source radius, and static stress drop from the plateau level and the corner-time and of the average logarithm of P-wave displacement versus time with the assumption of a triangular moment rate function, uniform rupture speed, and constant/frequency-independent Q-factor. In the current paper, this time-domain methodology is implemented to a selected catalog of micro-earthquakes consists of 83 events with moment magnitude ranging between 1.0 and 1.5, occurred during 7 years (2007-2014) of fluid extraction/injection around Prati-9 and Prati-29 wells at The Geysers Geothermal field.

The rupture process of the recent moderate-to-large earthquakes in the Zagros area along the Iran plateau is investigated by analysing the strong motion data provided by the Iranian Building and Housing Research Centre (BHRC). The selected dataset includes the largest and deadliest 2017 Mw 7.3, Iran-Iraq (Ezgeleh) earthquake. The earthquake source parameters (moment magnitude, rupture duration and length, average slip, and static stress drop) are determined using a time-domain, parametric modelling technique based on the time evolution of the P-wave displacement signals. The earthquake source parameters are calculated from simulated triangular moment-rate functions assuming the circular source models for a constant rupture velocity. The anelastic attenuation effect is modelled through the independent frequency-Q parameter ranging from 50 to 200 and accounted for by a post-processing procedure that retrieves the attenuation-corrected, moment-rate triangular shape. Results show that the average static stress-drop with different \({Q}_{P}\), varies between =0.9 (0.7 − 1.2) MPa and =1.6 (1.2 − 2.0) MPa. Assuming a circular rupture model for Ezgeleh earthquake, we estimate a moment magnitude of 6.9, rupture duration of 7 seconds, source radius of 16 km, average slip of about 2 m and static stress drop of 3.4 MPa.

With the aim to investigate the rupture complexity and the radiated wave field of 2017, Mw 3.9, Ischia earthquake, south-west of Naples (Italy), we used finite-fault modeling to invert the near-source (and searched for the best-fit kinematic rupture parameters. This analysis showed that the rupture nucleated at about 600 m west of IOCA and 1.1-km depth, along a 1 km, NW-SE striking fault (i.e., thrust with right-lateral component), with a rupture velocity of about 0.7 km/s. The retrieved rupture model coupled with multipath reverberations effects related to a thin, low-velocity near-surface volcanic sedimentary layer, well explains the observed long ground motion duration and the large amplitudes recorded all over the island. Finally, the apparent source time function (STF), obtained from inverse modeling using a theoretical Green’ function (GF), is validated by implementing an empirical GF (EGF) analysis.

Fault zones are major sources of hazard for many populated regions around the world. Earthquakes still occur unanticipated, and research has started to observe fault properties with increasing spatial and temporal resolution, having the goal of detecting signs of stress accumulation and strength weakening that may anticipate the rupture. The common practice is monitoring source parameters retrieved from measurements; however, model dependence and strong uncertainty propagation hamper their usage for small and microearthquakes. Here, we decipher the ground motion (i.e., ground shaking) variability associated with microseismicity detected by dense seismic networks at a near-fault observatory in Irpinia, Southern Italy, and obtain an unprecedentedly sharp picture of the fault properties evolution both in time and space. We discuss the link between the ground-motion intensity and the source parameters of the considered microseismicity, showing a coherent spatial distribution of the ground-motion intensity with that of corner frequency, stress drop, and radiation efficiency. Our analysis reveals that the ground-motion intensity presents an annual cycle in agreement with independent geodetic displacement observations from two Global Navigation Satellite System stations in the area. The temporal and spatial analyses also reveal a heterogeneous behavior of adjacent fault segments in a high seismic risk Italian area. Concerning the temporal evolution of fault properties, we highlight that the fault segment where the 1980 Ms 6.9 Irpinia earthquake nucleated shows changes in the event-specific signature of ground-motion signals since 2013, suggesting changes in their frictional properties. This evidence, combined with complementary information on the earthquake frequency–magnitude distribution, reveals differences in fault segment response to tectonic loading, suggesting rupture scenarios of future moderate and large earthquakes for seismic hazard assessment.

The imaging of volcanic systems is a challenging topic that attracts the scientific community’s attention. The characterization of structures and rock properties by means of seismic active methods is becoming fundamental for providing ultra-high-resolution images of the structures of interest. The Solfatara Volcano is a quiescent volcano in the Campi Flegrei resurgent nested caldera that is continuously under investigation and monitoring for its shallow activity, such as fumaroles. The purpose of this work is to characterize the fluid accumulation zone in the first 150 m depth in the middle of the crater, using several post-stack seismic attributes and Amplitude Versus Offset (AVO) analysis to characterize the contact between the CO2 and condensed water in the shallower accumulation zone. The two 400 m-long profiles to which we refer in this work have been acquired during the active Repeated InduCed Earthquakes and Noise experiment. The profiles were deployed along with the NNE-SSW and WNW-ESE directions across the whole surface of the crater including the main surface anomalies of the fumaroles, in the eastern area, and the mud-pool of Fangaia, located in the western area. The seismic pre-processing, pre-stack processing, and post-stack analysis previously applied on the NNE-SSW profile are here performed for the first time on the WNW-ESE profile, while partial-stack AVO analysis is performed for both profiles. The post-stack attributes including time gain, envelope, energy, and root mean square have been computed and extracted for determining the maximum and minimum values of amplitude zones on the migrated post-stack seismic profiles. Such anomalies are provided by complex and geometrical attributes embedding information on faults and chaotic zones. The AVO technique has also been used as a direct gas indicator to enhance fluid discrimination and identification. Finally, the analysis of the profile, seismic attributes, and near-surface structural interpretation related to the Solfatara Volcano has been incorporated into the proposed analysis. The multi-2D image depicts fluids trapped in the Solfatara Volcano at depths ranging from 10 to 50 m below the crater’s surface, as well as their migration paths up to 150 m deep: this evidenced contact between the fluids has been probably due to the solfataric alteration of the minerals, caused by the arising plume and the abovecondensed water which decreases the permeability of the rocks and forms an argillic phase working as cap-rock and trapping the gases. The application of the AVO analysis, coupled with the seismic attribute’s investigation, provides a very detailed multi-2D image of the shallower Solfatara Volcano, which outperforms in terms of accuracy the ones obtained with different tools in previous works, and that evidences the presence and the position of the liquid and the gases in the north-east area of the Solfatara Volcano.

The West Delta Deep Marine (WDDM) concession is one of the abundant natural gas resources in the world characterised by the presence of several active gas chimneys conduit feeding pockmarks. The detection of shallow gas accumulations has been gaining importance in hazard assessments before and during offshore drilling operations, whereas there is no way to estimate the exact pressure of the gas content in sediment to expect the potential gas hazards before and during the offshore installations, operations, and drilling. Monitoring of the gas chimneys and pockmarks plays an important role as an early warning for the oil industry to more focus on this kind of activities which may represent a catastrophic event in the future for the offshore installations at the WDDM region. Moreover, the “‘return period” of the pockmark activities is a region-dependence parameter according to the continuity of the gas supply and stability of the seepage pathway. However, in this study, the identification of the direct and indirect evidence of the shallow gas presence and migration pathways to the seafloor is achieved by extracting various-chosen seismic attributes, such as Root Mean Square, envelope, energy, the cosine of the instantaneous phase, variance, and chaos attributes. These attributes improve the imaging of several seismic evidence such as bright anomalies, enhanced reflectors, gas chimneys, and associated seabed features formed by the migration of the fluids from deep reservoirs through gas chimneys up to the seafloor. The presented profiles clearly show that gas chimneys and pockmarks combined with other associated features represent common features of the WDDM concession that can severely impact during and after offshore drilling operations in the aspects of safety, environment, and cost.

The offshore part of the Nile Delta is considered one of the most prolific provinces for gas production and for future petroleum exploration. Amplitude Variation with Offset (AVO) analysis supported by composite logs considered as one of the best-advanced techniques enables the interpreter to understand the seismic data. It is used to generate a new view of the output results, especially for the identification of gas zones as gas channels by using pre-stack AVO attributes that based on the intercept product gradient (A*B) and the Scaled Poisson’s Ratio Change. Free gas, regardless of the percentage show obvious AVO anomaly. Well log data, including gamma-ray, resistivity, and Vp sonic logs are used in the seismic data to well tie and in the generation of the synthetic seismogram. Seismic data conditioning processes with check-shot correction is performed to improve the resolution of the reflection events and signal to noise ratio. AVO attributes technique, as a direct hydrocarbon indicator, including AVO gradient analysis and AVO crossplot separate the gas levels in the sand-shale sequences. The identified gas-bearing zones consistent with well log data responses. As the main conclusion, we show the visual evidence for the gas-bearing zones by interpreting different AVO responses due to the changes in fluid and rock types.

Seismic attributes supported by composite logs are the best way that can enable the interpreter to understand seismic data very well and generate a new view of the output results. Detection of the reservoir zone can be enhanced by analyzing wells log data based on Gamma-ray, Resistivity, and Vp sonic logs respectively. Composite logs of Scarab-1, Scarab-De, Scarab-Da, Scarab-Dd, and Scarab-2 wells indicate the lateral and vertical variation of the gas reservoir in El Wastani Formation. However, there are several seismic attributes that can be used to support reservoirs identification. For enhancement the detection of the hydrocarbon reservoirs, it is important to carefully analyze the 2D seismic data, which in this study will be primarily prepared to enhance seismic attributes results for the identification of gas chimneys, gas zones as channels, enhance stratigraphic and structural interpretations. In this article, we have performed data conditioning, quality control and seismic well ties including the preliminary wavelet extractions to get accurate output. Then, we have extracted of several classes of physical, geometrical and complex attributes as a direct hydrocarbon indicator to identify the gas zones, channels and chimneys and to identify the faults and discontinuities. The main contribution of this work is to provide a more detailed seismic reflection image supported by several seismic attributes classes and well logs to show a visual and quantitative evidence to identify the gas channels and gas chimneys with improving the detection of the faults and discontinuities. Keywords: Seismic attributes, Offshore nile delta, Gas channels, Gas bearing sand zones, Gas chimney, Well logging

Repeated tomographic inversions in time (the so called 4D tomography) track physical properties and stress changes in the medium hosting fault systems by measuring changes in P and S seismic velocities. These changes may provide insights on fault system dynamics and earthquake triggering mechanisms. We applied 4D tomography to the volume embedding the Irpinia Fault System (IFS, southern Italy) using more than ten years of continuous seismicity monitoring. The IFS is one of the Italian most hazardous fault systems, being able to generate the 1980 Ms 6.9 earthquake, characterized by a multi-segmented rupture. Seismicity was divided into uneven epochs having almost the same spatial resolution of the volume hosting the IFS.The resulting images show time-invariant features, clearly related to crustal lithology, and time-changing (up to 20%) velocity anomalies in the central region. Vp, Vs and Vp/Vs anomalies are referred to the tomographic model obtained using all the data set, and occur at depths ranging between 1 and 5 km, and between 8 and 12 km. These anomalies are temporally well-correlated with groundwater recharge/discharge series and geodetic displacements during the same time intervals. This correlation provides evidence for the existence of pulsating pore pressure changes in a fractured crustal volume at depth of 8-12 km, saturated with a predominant gas phase (likely CO2) and correlated with groundwater recharge processes, We suggest that tomographic measurements of the Vp-to-Vs spatiotemporal changes are a suitable proxy to track the pore pressure evolution at depth in highly sensitive regions of fault systems.

The estimation of spatial and temporal changes in the host medium physical properties is a quest to improve risk evaluation and hazard forecasting application. The space-time evolution of the seismicity gives information about stress variations, fluid content, and pore-pressure changes inside the medium. Thus, the accuracy of arrival-time measurements is crucial for travel-time-based seismological applications, such as earthquake location and travel(delay)-time tomography, especially when double-difference times are used. Standard monitoring networks and tools implements single-station, STA/LTA-based, automatic event detection/location procedures, which may produce inconsistent arrival-times of the same phase among stations. To overcome this problem, refined cross-correlation (CC) techniques for time picking have been recently developed. Their basic approach is to use CC to refine picks of event pairs with high waveform similarity. Similar events are grouped in families, considering the max CC values, the inter-distance and/or the focal mechanism similarity. Two drawbacks of this common approach are (1) the impact of noise from individual receiver levels on the quality of reference trace (RT) and (2) the inability to adjust the systematic shift of automatic picks.Here we propose a new, fully automatic approach to refine the phase time picks. The CC is used to identify family members with a hierarchical clustering procedure. In each family, after the trace alignment, we build the RT by stacking the events weighted by the signal-to-noise ratio and the polarity. We applied this technique to a catalog of 3574 events of the 2014 MJMA 6.7 sequence occurred at the Northern Nagano prefecture. The results indicate that we can improve the precision of phase picks of similar events and to adjust the systematic shift introduced by the automatic picker with mean differences between refined and automatic picks up to 0,5-1 s.The high consistency of the phase picks allows to increase the accuracy of absolute location by reducing the mean location error from 0,6 km to 0,1 km and the root-mean-square from 0,15 to 0,075. Consequently, we observe an alignment of the seismicity respect to the main fault plane with an 30°-45° east-dipping angle for the shallow part while the deeper part dips at 50°-65°. Then, the double difference location provides highly resolved hypocenter locations and medium parameters by considering events of the same family as events pair. This improvement allows to use fast-tracking methods, as the Vp/Vs in time and the Coda-Wave Interferometry, to get information about the velocity variations before and during the sequence. By using those methods, we expect to get accurate information of the physical properties evolution and especially about the role of fluid in the triggering of the sequence.

The imaging of volcanic structures by means of seismic techniques is aimed at the structural characterization and monitoring purposes. The quiescent volcano of the Solfatara belong to the caldera of the Campi Flegrei Italy, a resurgent nested caldera that has been extensively investigated through active seismic investigation.The fumaroles of Bocca Grande and Bocca Nuova at the Solfatara volcano, represent some of the main markers of deep magmatic shallow hydrothermal activity. In this article we identify the gas accumulation zone using the attributes and scaled Poisson ratio extracted from multi-2D seismic profiles. The 400 m long profiles, have been acquired during the active experiment RICEN (Repeated Induced Earthquake and Noise) performed in the context of the EU project MEDSUV between May and November 2014. The seismic arrays were deployed along the NE-SW and NW-SE directions within the crater across the zones of the fumaroles and the “fangaia”.The time- and depth-sections are reconstructed after applying residual statics, DMO corrections, CMP gathering, and the post-stack Kirchhoff migration technique. The energy, root mean square, envelope, and sweetness attributes have been computed and extracted for determining the maximum and minimum values of amplitude zones on the migrated, post-stack seismic sections. Furthermore, we have investigated the time-gain attribute, which is used to interpret deep reflectors, and the variance attribute, that is a geometrical attribute providing information on location of faults, discontinuities, and chaotic zones. To better detail the reflectivity of shallow events, enhanced by the post stack attributes, the Amplitude Versus Offset (AVO) technique has also been used to discriminate and identify shallow gas pockets. The seismic profile, seismic attributes, and near-surface structural interpretation of the Solfatara volcano have been combined into a final structural image of the Solfatara subsoil. This show a clear evidence of the fluids trapping zones at 10-50 m depth beneath the crater's surface, as well as their migration paths down to 150 meters depth.

We developed a Bayesian technique to infer the double-couple, focal mechanism parameters (strike, dip and slip angles) of an earthquake source. The method uses 3 independent datasets: P-wave peak amplitude and polarity and S-to-P amplitude ratio wherever it is available.The Bayesian technique works even in absence of one dataset and easily integrates any prior information about the region of study. The parameter space is explored thanks to an octree strategy. The method estimates the Posterior pdf, where the maximum likelihood parameter values (MAP model) both for the principal and auxiliary plane are chosen as the final fault mechanism solution. Furtherly, the uncertainties as the projections of the semi-axis of the 68% confidence ellipsoid centred on the MAP model are provided.The joint use of the three datasets allows to determine a solution even in the case of a limited number of stations that have recorded the event, which is the case for example for small magnitude earthquakes (MWe applied and tested the methodology to a microearthquake sequence (ML 0.4-3.0) occurred in the Irpinia region, South Italy, using an uninformative prior distribution for the parameters. In this area, the background seismicity occurs in a volume delimited by the faults activated during the 1980 Irpinia M 6.9 earthquake. This faults system is complex and composed of northwest–southeast striking normal faults along the Apennines chain. A network of 3-component accelerometers and velocimeters is currently monitoring the area (Irpinia Seismic NETwork).We inferred the focal mechanism of the earthquakes of the sequence. Our results show fault mechanism solutions which are consistent with previous studies, well reflecting the regional stress field. The focus on micro-seismicity can reveal characteristics useful to highlight behaviours of larger scale seismicity.

We present a comprehensive review of seismic and gravity observations and tomographic models produced over the past four decades in order to understand the structure of the crust beneath the Campi Flegrei caldera. We describe the main lithological and structural discontinuities defined through these observations, illustrate their geophysical responses, and discuss the constraints they give to the understanding of magmatic and volcanic processes. Micro-seismic crises related to caldera unrest, and ambient seismic noise measurements provide comprehensive seismic data to local earthquake and ambient noise tomography. In combination with reflection data from onshore and offshore active seismic experiments, velocity tomography reconstructs the elastic properties of the caldera between surface and ~4 km depth. Active experiments also define the depth of lithological interfaces and deep (~7.5 km) partially molten bodies. Seismic attenuation tomography provides information complementary to velocity tomography, defining lateral lithological changes and the geometry of onshore and offshore fluid and magma bodies down to 4 km depth. Once compared with seismic analyses, gravity data highlight lateral changes in the offshore caldera structures. During the deformation and seismo-geochemical unrest (1982–1984), they permitted to reconstruct a minor (

Earthquake early warning systems are able to issue an alert just after the start of the seismic rupture on the fault plane, but before the ground shaking reaches the sites to be protected. The available lead-time for security actions is very short (seconds to several dozens of seconds), requiring fast and robust methods to make these systems operational. Here, general principles about the two paradigms of early warning systems are presented: the regional and the on-site systems. When these methods are applied to data recorded by very dense networks, such as in near-fault observatories, the blind zone can be shortened to 15–25km. Next generation of early warning systems should reduce the epistemic variability by implementing modeling of finite-source and site effects. Finally, the combination of on-site and regional systems may lead to a real-time estimation of the ground-shaking maps, overcoming the problem of computing the event location, and magnitude.

The reliable determination of earthquake source parameters is a relevant task of seismological investigations which ground nowadays on high-quality seismic waveforms collected by near-source dense arrays of ground motion sensors. Here, we propose a parametric modeling technique which analyzes the time-domain P-wave signal recorded in the near-source range of small-to-large-size earthquakes. Assuming a triangular moment rate function, a uniform speed, and circular rupture model, we develop the equations to estimate the seismic moment, rupture radius, and stress drop from the corner time and plateau level of the average logarithm of the P-wave displacement versus time curves (LPDT). The constant- Q , anelastic attenuation effect, is accounted by a postprocessing procedure that evaluates the Q -unperturbed moment rate triangular shape. The methodology has been validated through application to the acceleration records of the 2016-2017 Central Italy and 2007-2019 Japan earthquake sequences covering a wide moment magnitude range (Mw 2.5-6.5) and recording distance 5.5 events in Central Italy relative to previous estimates using spectral methods.

Water injection in geothermal areas is the preferential strategy to sustain the natural production of geothermal resources. In this context, monitoring microearthquakes is a fundamental tool to track changes in the reservoirs in terms of soil composition, response to injections, and resource exploitation with space and time. Therefore, refined source characterization is crucial to better estimate the size, source mechanism, and rupture process of microearthquakes, as they are possibly related to industrial activities, and to identify any potential variation in the background seismicity. Standard approaches for source parameter estimation are ordinarily based on the modelling of Fourier displacement spectra and its characteristic parameters: the low-frequency spectral level and corner frequency. Here, we apply an innovative time domain technique that uses the curves of P-wave amplitude vs. time along the seismogram. This methodology allows estimation of seismic moment, source radius, and stress release from the plateau level and the corner time of the average logarithm of P-wave displacement versus time with the assumption of a triangular moment rate function, uniform rupture speed, and a constant/frequency-independent Q-factor. In the current paper, this time domain methodology is implemented on a selected catalog of microearthquakes consisting of 83 events with a moment magnitude ranging between 1.0 and 1.5 that occurred during a 7-year period (2007–2014) of fluid extraction/injection around Prati-9 and Prati-29 wells at The Geysers geothermal field. The results show that the time domain technique provides accurate seismic moment (moment magnitude) and rupture duration/radius estimates of microearthquakes down to the explored limit (M 1) while accounting for the anelastic attenuation effect in the radiated high-frequency wavefield. The retrieved source radius vs. moment scaling is consistent with a self-similar, constant stress drop scaling model, which proves an appropriate attenuation correction and the validity of the assumed, triangular moment rate function for microearthquake ruptures. Two alternative mechanical models are proposed to explain the observed difference (about two orders of magnitude) in the retrieved average stress release estimates between the time and frequency domain methods. We argue that the two quantities may not refer to the same physical quantity representing the stress release of earthquake ruptures. Either the smaller stress release values from the time domain method may indicate a larger fracture area (by a factor of 20) radiating the observed P-waveforms than the one estimated from the corner frequencies, or the frequency domain estimate is a proxy for dynamic stress release while the time domain is more representative of the static release. The latter is associated with a much lower dynamic friction value than static friction value at the fault during the rupture process.

In this study we implemented and tested the Earthquake Early Warning system PRESTo (PRobabilistic and Evolutionary early warning System, Satriano et al., 2011) on the Greek Ionian islands of Lefkada, Zakynthos and Kefalonia. PRESTo is a free and open source platform for regional Earthquake Early Warning developed at the University of Naples Federico II, which is currently under experimentation in Southern Italy, in the area covered by the Irpinia Seismic Network. The three Ionian islands selected for this study are located on the North-Western part of the Hellenic trench. Here the seismicity rate and the seismic hazard, coupled with the vulnerability of existing critical infrastructures, make this region among the highest seismic risk areas in Europe, where the application of Earthquake Early Warning systems may become a useful strategy to mitigate the potential damage caused by earthquakes. Here we studied the feasibility of implementing an Earthquake Early Warning system on an existing seismic network, which was not specifically made for earthquake early warning purposes, and evaluated the performance of the system, using a data set of real-earthquake recordings. We first describe the technical details of the implementation of PRESTo in the area of interest, including the preliminary parameter configuration and the empirical scaling relationship calibration. Then we evaluated the performance of the system through the off-line analysis of a database of real earthquake records belonging to the most recent M > 4.0 earthquakes occurred in the area. We evaluated the performance in terms of source parameter estimation (location, magnitude), accuracy of ground shaking prediction and lead-time analysis. Finally, we show the preliminary results of the real-time application of PRESTo, performed during the period 01–31 July 2019.

In the West Delta Deep Marine (WDDM) concession many important gas reservoirs have been recently discovered. To improve the possibility of discovering new natural gas resources, an integrated predi...

The continuous monitoring of the space-time-magnitude evolution of seismicity is a crucial task to assess the geo-mechanical conditions of hydrocarbon reservoirs. It is fundamental to design optimized high-sensitivity and cost-effective seismic networks able to detect and locate low magnitude events with high accuracy. In Italy, after the concern for the 2012 Emilia earthquake, the government released the guidelines for monitoring the seismicity in areas surrounding subsurface industrial activities. In this work, we propose an optimization study for seismic monitoring networks based on the guideline requirements. We evaluated the performance, in terms of detection/location thresholds and events location errors, of different network layouts constructed by varying the station density and geometry and considering also the integration of seismic arrays. We simulated sets of seismic sources at different depths by varying magnitude and stress drop values. We considered two different values of noise level at the stations. The results show that the station density and the noise level represent the crucial parameters for the seismic network performances. The performances of a standard network comply the guidelines requirements in terms of detection/location thresholds. Only the integration of seismic networks with arrays allows to decrease the location errors of several hundreds of meters and to reach the location accuracy required by the Italian guidelines. We foresee the integration of standard networks with seismic arrays to achieve high performance in terms of detection capability and location accuracy.

The performance of an earthquake early warning system (EEWS) for southern Iberia during the period of 2016–2019 is analyzed. The software PRESTo (PRobabilistic and Evolutionary early warning SysTem; the University of Naples Federico II, Italy) operating at the Universidad Complutense de Madrid has detected 728 events (2 < Mw < 6.3), with 680 earthquakes occurring in southern Iberia. Differences between the EEWS origin time and epicenter and those of the Instituto Geográfico Nacional (IGN) catalog are less than 2 s and 20 km, respectively, for 70% of the detected earthquakes. The main differences correspond to the EEWS magnitude that is underestimated for earthquakes that occurred at the west of the Gibraltar Strait (Mw differences larger than 0.3 for 70%). To solve this problem, several relationships have been tested, and a modification to those that currently use PRESTo is proposed. Other improvements, such as to densify the network or to use 3D Earth models, are proposed to decrease the time needed to issue the alert and avoid the false alerts (19 events over a total of 728 events). The EEWS has estimated the depth for 680 events and compared to those from the IGN (491 events). The performance of PRESTo during the 2020–2021 Granada swarm is analyzed. The hypocentral locations for the three largest earthquakes are close to those from the IGN (differences from 1 to 7 km for the epicenter and 0 s for the time origin), although there are some differences in their magnitude estimations that varies from 0.2 to 0.5. The PRESTo first times are 17, 25, and 41 s after the origin time. This study shows that the actual PRESTo EEWS configured for the southern Iberia may generate effective warnings despite the low seismicity rate in this region. To decrease the warning time, the geometry and density of the seismic network must be improved together with the use of 3D Earth models and on-site system approaches.

The reliable determination of earthquake source parameters is a relevant task of seismological investigations which ground nowadays on high quality seismic waveforms collected by near-source dense arrays of ground motion sensors. Here we propose a parametric modelling technique which analyzes the time-domain P-wave signal recorded in the near-source range of small-to-large size earthquakes. Assuming a triangular moment-rate function and a uniform speed, circular rupture model, we develop the equations to estimate the seismic moment, rupture radius and stress-drop from the corner-time and plateau level of the average logarithm of the P-wave displacement vs time curves (LPDT). The constant-Q, anelastic attenuation effect is accounted by a post-processing procedure that evaluates the Q-unperturbed moment-rate triangular shape.The methodology has been validated through the application to the acceleration records of the 2016-2017 Central Italy and 2007-2019 Japan earthquake sequences covering a wide moment magnitude range (Mw 2.5 - 6.5) and recording distance < 100 km. After correcting for the anelastic attenuation function, the estimated average stress-drop and the confidence interval (〈∆σ〉=0.60 (0.42-0.87) MPa and 〈∆σ〉=1.53 (1.01-2.31) for crustal and subcrustal events of Japan and 〈∆σ〉=0.36(0.30-0.44) MPa for Central Italy) show, for both regions, a self-similar, constant stress-drop scaling of the rupture duration/radius with seismic moment. The smaller sensitivity of the spatially averaged, time-varying peak displacement amplitude to the radiation from localized high slip patch on the fracture surface, could explain the retrieved smaller average stress-drops for sub-crustal earthquakes in Japan and M>5.5 events in Central Italy relative to previous estimates using spectral methods.

A primary task of a network-based, earthquake early warning system is the prompt event detection and location, needed to assess the magnitude of the event and its potential damage through the predicted peak ground shaking amplitude using empirical attenuation relationships. Most of real-time, automatic earthquake location methods ground on the progressive measurement of the first P-wave arrival time at stations located at increasing distances from the source but recent approaches showed the feasibility to improve the accuracy and rapidity of the earthquake location by using the additional information carried by the P-wave polarization or amplitude, especially with unfavorable seismic network lay-outs. Here, we propose an evolutionary, Bayesian method for the real-time earthquake location which combines the information derived from the differential P-wave arrival times, amplitude ratios and back-azimuths measured at a minimum of two stations. As more distant stations record the P-wave, the posterior pdf is updated and new earthquake location parameters are determined along with their uncertainty. To validate the location method, we performed a retrospective analysis of mainshocks (M > 4.5) occurred during the 2016–2017 Central Italy earthquake sequence by simulating the typical acquisition layouts of in-land, coastal and linear array of stations. Results show that with the combined use of the three parameters, 2–4 s after the first P-wave detection, the method converges to stable and accurate determinations of epicentral coordinates and depth even with a nonoptimal coverage of stations. The proposed methodology can be generalized and adapted to the off-line analysis of seismic records collected by standard local networks.

In this work we propose and apply a straightforward methodology for the automatic characterization of the extended earthquake source, based on the progressive measurement of the P-wave displacement amplitude at the available stations deployed around the source. Specifically, we averaged the P-wave peak displacement measurements among all the available stations and corrected the observed amplitude for distance attenuation effect to build the logarithm of amplitude vs. time function, named LPDT curve. The curves have an exponential growth shape, with an initial increase and a final plateau level. By analyzing and modelling the LPDT curves, the information about earthquake rupture process and earthquake magnitude can be obtained. We applied this method to the Chinese strong motion data from 2007 to 2015 with Ms ranging between 4 and 8. We used a refined model to reproduce the shape of the curves and different source models based on magnitude to infer the source-related parameters for the study dataset. Our study shows that the plateau level of LPDT curves has a clear scaling with magnitude, with no saturation effect for large events. By assuming a rupture velocity of 0.9 Vs, we found a consistent self-similar, constant stress drop scaling law for earthquakes in China with stress drop mainly distributed at a lower level (0.2 MPa) and a higher level (3.7 MPa). The derived relation between the magnitude and rupture length may be feasible for real-time applications of Earthquake Early Warning systems.

Seismic sequences are a powerful tool to locally infer geometrical and mechanical properties of faults and fault systems. In this study, we provided detailed location and characterization of events of the 3&ndash, 7 July 2020 Irpinia sequence (southern Italy) that occurred at the northern tip of the main segment that ruptured during the 1980 Irpinia earthquake. Using an autocorrelation technique, we detected more than 340 events within the sequence, with local magnitude ranging between &minus, 0.5 and 3.0. We thus provided double difference locations, source parameter estimation, and focal mechanisms determination for the largest quality events. We found that the sequence ruptured an asperity with a size of about 800 m, along a fault structure having a strike compatible with the one of the main segments of the 1980 Irpinia earthquake, and a dip of 50&ndash, 55&deg, at depth of 10.5&ndash, 12 km and 60&ndash, 65&deg, at shallower depths (7.5&ndash, 9 km). Low stress drop release (average of 0.64 MPa) indicates a fluid-driven initiation mechanism of the sequence. We also evaluated the performance of the earthquake early warning systems running in real-time during the sequence, retrieving a minimum size for the blind zone in the area of about 15 km.

Seismic arrays are instruments capable to lower the magnitude threshold of earthquake detection by improving the signal-to-noise ratio of recordings. Seismic arrays have been used since 1960s, to investigate global earthquakes or small-scale structure of the Earth’s interior. We designed a cost-effective seismic monitoring array-system made by autonomous stations specifically designed for studying local micro-seismicity. The data collected by this system allow to develop and apply a new method for earthquake detection and location of micro-seismicity based on a frequency-wavenumber (f-k) domain analysis of continuous data recorded by small seismic arrays, in order to separate the coherent signal of low magnitude events from the surrounding noise.Field surveys have been carried out in two Italian regions, which are seismically active and already monitored by high quality, standard seismic networks, so to allow us to test the performance of the proposed array configuration and processing algorithm.The first survey was carried out in the Irpinia region (Southern Italy), near the main fault segment activated during the Ms 6.9 Irpinia earthquake occurred in 1980. The natural seismicity of the area features occasional small seismic sequences, with magnitude (ML) less than 3, that are recorded by the local seismic network that monitors the Irpinia fault-system (ISNet - Irpinia Seismic Network). Three small aperture seismic arrays (few hundred meters wide) were deployed at distance of few tens of kilometers each other for three months. Each array was made up of seven 3-component stations, arranged in irregular geometry.The second experiment was carried out in the Montello-Collalto area (Veneto region, North-East Italy), where an underground gas storage concession, known as “Collalto Stoccaggio”, exists. The gas storage activity is monitored by a local seismic network named “Collalto Seismic Network” (Rete Sismica di Collalto, or RSC). This dense network was designed and is managed by the National Institute of Oceanography and Applied Geophysics (OGS) on behalf of Edison Stoccaggio S.p.A., the storage concession holder. A seismic array composed of eight 3-component stations with 2 km of maximum aperture was deployed for a couple of months to monitor the micro-seismicity occurring nearby.Our preliminary results suggest that the f-k earthquake detection algorithm of micro-seismicity using seismic arrays can become a valid tool to complement standard seismic networks in monitoring and studying natural and induced seismicity. In the Irpinia region, for instance, we have detected and located about six times the earthquakes recorded by the local network lowering the magnitude down to 0.1, smaller than the catalogue minimum magnitude that is equal to 1.2.

The anelastic attenuation of rocks strongly depends on the contained fluid physical state and saturation. Furthermore, it is more sensitive than elastic parameters to changes in the physical state of materials. In a geologically complex volcanic context, where fluids play a very important role, anelastic imaging of the subsoil is therefore a very powerful tool for a better understanding of its dynamics.In this study we present a robust workflow aimed at retrieve accurate 1-D and 3-D anelastic models from the processing of active seismic data, in terms of lateral and depth variations of P-wave quality factors QP. This methodology has been applied to data collected during a high resolution active seismic experiment in a very small-scale volcanic volume, the Solfatara crater, within Campi Flegri caldera, Southern Italy. The presented methodology is developed in three distinct steps: 1) the active seismic data have been properly processed and analyzed for measuring the t* attenuation parameter for all possible source-receivers couples. First, the source contribution has been removed by cross-correlating the recorded signal with the sweep function of the Vibroseis, which was the adopted active seismic source. Then, the spectral decay method has been applied in order to compute the t* values. 2) A reference 1-D attenuation model has been retrieved by means of a grid search procedure aiming at finding the 1-D Qp structure that minimizes the residual between the average observed t* and the theoretical t* distributions. The obtained starting reference model allowed to build a preliminary map of t* residuals through which the retrieved t* dataset has been validated. 3) The 15,296 t* measurements have been inverted by means of a linearized, perturbative approach, in a 160 x 160 x 45 m3 tomographic grid.The retrieved 3-D attenuation model describes the first 30 m depths of Solfatara volcano as composed of very high attenuating materials, with Qp values ranging between 5 and 40. The very low Qp values, correlated with low Vp values retrieved by a previous tomographic work carried out in the area, indicate the low consolidation degree of very superficial volcanic materials of Solfatara volcano. Finally, in the NE part of the crater, lower attenuating bodies have been imaged: it is a further hint for characterizing this area of the volcano as the shallow release of the CO2 plume through the main fumaroles of the crater.

The Irpinia Near Fault Observatory (NFO) is an EPOS infrastructure located in the Campania-Lucania Region (Southern Italy). Its goal is to characterize the microseismicity and to understand the underlying chemical and physical processes occurring along the fault systems that can potentially generate large earthquakes in the area. The Irpinia NFO is currently composed of ISNet – Irpinia Seismic Network, with associated products and services. ISNet is a local network of 32 accelerometric, short-period and broad band stations, that cover the seismogenic areas related to the main earthquakes that occurred in the region in the last centuries, including the 23 November 1980 , Ms = 6.9 event. Also, ISNet provides real-time analysis and it represents the prototype network for the testing of early warning systems in Italy.Here we present tools and techniques to accurately locate and characterize the seismicity within the Observatory. Accurate event detection of weak signals from small magnitude events is based on the coherence of arrival times and migration techniques. This method is then coupled with advanced picking and double differences techniques to accurately locate events with a sub-kilometric scale resolution. Source parameters are thus computed inverting the displacement amplitude spectrum, with a probabilistic approach based on the conjunction of states of information in the data and model spaces. This technique is able to automatically rule out unconstrained solutions, while accounting for correlation among parameters. Source location and characterization is here used to investigate the role of the fluids in the region embedding the fault systems; space and time changes in the medium properties or in the source parameters can be used to detect a deviation from the present mechanical state of the faults owing to changes in fluid pore pressure and migration.Finally, local dense arrays are used here to improve our capability to detect events within the noise level and to move from a point-source to an extended source description of small events in the area.

The imaging of seismic reflection data provides a powerful high-resolution method for studying volcano structure and fluids presence. The shallow structure of the Solfatara crater, a surface marker of deep magmatic activity inside Campi Flegrei caldera (Southern Italy), is characterized in terms of seismic profile and attributes. The main contribution of this work is to provide a detailed and improved seismic reflection image of the Solfatara crater and the identification of gas accumulation. The profiles are deployed along the NNE-SSW directions, the first, and the second orthogonal to the last. The two profiles are 400 m long acquired during the active experiment RICEN (Repeated Induced Earthquake and Noise) performed in the framework of the EU project MEDSUV between May and November 2014. Pre-stack processing of the seismic data has been performed in order to remove the noisy traces, low-frequency noise and reduce the ground roll phases. A very detailed velocity analysis for the NMO correction has been performed with the integration of information derived from the Vp velocity model previously obtained by the non-linear Bayesian technique. After having applied residual statics and DMO corrections, the CMP gathering, the post-stack Kirchhoff migration technique was performed to produce the final seismic profiles in time and depth. Once having obtained the post-stack migrated imaged, the energy, root mean square, envelope and sweetness attributes were computed for defining the maximum and minimum value of amplitude zones. In addition, other attributes as the time-gain attribute in order to interpret the deep reflectors and the variance attribute to define the faults, discontinuities, and chaotic zones have been evaluated. To enhance fluids identification the Amplitude Versus Offset (AVO) variation technique has been further applied to identify the gas zone in the explored sections. By integrating all information from the original seismic profile, seismic attributes and geophysical investigation relative to the Solfatara volcano, the multi-2D image presents the fluids trapped in the Solfatara crater at depths between 10 to 50 m below the surface of the crater and their migration pathways up to 150 meters depth.

This study focuses on the the active fault system that caused the 1980 M_S 6.9 Irpinia earthquake (Irpinia fault zone (IFZ)) that is presently interested by a continuous and frequent micro-earthquake activity occurring within the volume in the volume enclosed by two antithetic faults. It is therefore important to improve the knowledge of the IFZ dynamics, with reference to potential future occurrence of moderate to large earthquakes, especially in terms of earthquake triggering mechanisms. Several previous works evaluated the spatial distribution of elastic/anelastic fault-embedded medium properties and related rock physical micro-parameters in connection with the seismicity rate. These studies showed a spatial correlation between high Vp/Vs, low seismic attenuation in rock volumes where most of seismicity occurs, suggesting that fluid-driven pore-pressure changes may plays a key role in controlling the seismicity production at the IFZ.Here we reconstruct accurate 4D seismic velocity images of the volume embedding IFZ which allows to detect and track space-time changes of medium elastic properties possibly induced by fluid pore pressure migration and investigate the related seismicity production.We analyzed the arrival time phase catalogue of about ten years (2005-2016) of Mw < 3.1 events recorded by the ISNet (Irpinia Seismic Network) and INGV network. We divided the catalog in 5 not-overlapping epochs by selecting in each of them , approximately the same number of events and an uniform volume coverage, in order to ensure that the 3D P and S velocity models could be equally well resolved for each epoch. By comparing the Vp, Vs and Vp/Vs images at each epoch in the equally resolved volume, we are able to detect medium velocity changes. Some regions, in the first 6 km of depth of NE part, do not show velocity changes with time, which is interpreted as the main effect of unperturbed lithology mainly controlling the average seismic velocity. In other regions, in the central part of the model at about 8-10 km depth, we clearly detect velocity changes causing an up to 10% Vp/Vs variation between different epochs. Based on the rock physical modelling, we associate the time-varying Vp/Vs and the observed amplitude of variation to fluid-driven changes in rock physical properties related to their spatial migration or pore-pressure induced changes. The regions where large Vp/Vs changes occur appear correlated with the largest seismicity production volumes, suggesting a direct link between the physical processes associated with fluid mobility and/or pore pressure migration and earthquake generation at the IFZ.

Machine learning techniques combined with multi-seismic attributes and well logs datasets have been successfully used in reducing the risk of drilling operations and petroleum exploration by providing precise petrophysical and seismic information extracted from the hydrocarbon reservoir rocks. For this purpose, Artificial Neural Networks (ANNs) work as a multi-channel processing system with a high degree of interconnection to classify various faces and predict the reservoir properties through the seismic profile by involving multi-seismic attributes and optionally well logs to the inputs. The main aim of this study is to use both supervised and unsupervised neural networks for the first time in the West Delta Deep Marine (WDDM) concession to identify the spatial dimensions of the gas-bearing channels and the detection of gas chimneys across the seismic profiles. We use back-error propagation algorithms of the Multilayer Perceptron (MLP) and self-organizing Unsupervised Vector Quantizer (UVQ) as supervised and unsupervised neural network methods, respectively, to detect the gas zones and channels, and to classify the gas chimneys and non-gas chimneys zones, as well as classification of the seismic reflections and lithologies. The output acquires a detailed analysis of the distribution pattern of gas channels and accurate information to image the gas chimneys. In the current study, the approach adopted is beneficial to image the gas chimneys and channels in different basins in any region of the world with similar geological settings.

We retrieve 3-D attenuation images of the crustal volume embedding the fault system associated with the destructive Ms 6.9, 1980 Irpinia earthquake by tomographic inversion of t* measurements. A high QP anomaly is found to be correlated with the 1980 fault geometry, while the QS model shows regional-scale variations related to the NE edge of the uplifted pre-Tertiary limestone. An upscaling strategy is used to infer rock properties such as porosity, consolidation, type of fluid mixing, and relative saturation percentage at 8–10 km fault depth. We constrain the porosity and consolidation in the ranges 4–5% and 5–9, respectively, with the possible fluid mixes being both brine-CO2 and CH4-CO2. The consolidation parameter range indicates high pore pressures at the same depths. These results support the evidence for a fracture system, highly saturated in gases and a seismicity triggering mechanism at the fault zone, which is strongly controlled by fluid-induced pore pressure changes.

We propose a P wave based procedure for the rapid estimation of the radiated seismic energy, and a novel relationship for obtaining an energy-based local magnitude (MLe) measure of the earthquake size. We apply the new procedure to the seismic sequence that struck Central Italy in 2016. Scaling relationships involving seismic moment and radiated energy are discussed for the Mw 6.0 Amatrice, Mw 5.9 Ussita, and Mw 6.5 Norcia earthquakes, including 35 ML > 4 aftershocks. The Mw 6.0 Amatrice earthquake shows the highest apparent stress, and the observed differences among the three main events highlight the dynamic heterogeneity with which large earthquakes can occur in Central Italy. Differences between estimates of MLe and Mw allows identification of events which are characterized by a higher proportion of energy being transferred to seismic waves, providing important real-time indications of earthquakes shaking potential.

Seismic imaging is used in this work, to reconstruct the shallow structure of the Solfatara crater, a surface marker of deep magmatic activity inside Campi Flegrei caldera (Southern Italy). We analyze the 1D orthogonal seismic arrays deployed in NNE-SSW directions for 400 m through the Solfatara crater during the recent active experiment RICEN (Repeated Induced Earthquake and Noise) performed in the framework of the EU project MEDSUV. Seismic data have been edited in the pre-stack stage by removing the noisy traces, low-frequency noise, and reduce the ground roll phases. Then, a velocity analysis has been carried out starting from the velocity spectrum to obtain a RMS velocity model, which has been followed by NMO, residual statics, and DMO corrections. We used the post-stack Kirchhoff migration technique before the extraction of the energy, root mean square, envelope and sweetness attributes defining the highest amplitude zones, the time-gain attribute in order to interpret the deep reflectors and the variance attribute to define the faults, discontinuities, and chaotic zones. Amplitude Versus Offset (AVO) analysis has been performed to identify the gas-saturated zone using partial angle-stacks, which is a benchmark to verify the presence of gas. The main contribution of this work is to provide a more detailed and improved seismic reflection image of the shallow depth of the Solfatara crater. The reliability of our velocity model has been assessed through the use of the Vp velocity model previously obtained by the non-linear Bayesian technique. This provides a final stack showing that the shallower minor faults and the extension of the major faults represent the main pathways for the uprising fluids. We present the visual evidence for the fluids trapped in the shallower part of the crater at depths between 20 and 50 m below the surface of the crater.

SUMMARYWhen a seismic rupture starts, the process may evolve into multiple ways, generating different size earthquakes. Contrasting models have been proposed to describe the evolution of the rupture process while limited observations at the scale of real earthquake data are available, so that a unifying theory is still missing. Here we show that small and large earthquake ruptures are different before the arrest and they do not exhibit a common, size-independent, universal behaviour. For earthquakes with magnitude 4

For network-based Earthquake Early Warning Systems (EEWS), the real-time earthquake location is crucial for a correct estimation of event location/magnitude and therefore, for a reliable prediction of the potential expected shaking at the target sites in terms of predicted maximum ground shaking. Different approaches have been recently proposed for the real-time location which mainly use absolute (or differential) P-wave travel times at a set of minimum available stations or measurement of the initial P-wave arrival time (Elarms, Presto, Horiuchi), polarization (Eiserman and Bock) or amplitude and time (Yamada). In this work, we propose a new method which is able to exploit the continuous, real-time information available from both time, amplitude and polarization of initial P-wave signals acquired by dense three component arrays deployed in the source zones. The methodology we propose is an evolutionary and Bayesian probabilistic technique that combines three different observed parameters: 1) the differential arrival times of P-waves (which are computed using a 1D velocity model for the estimation of the theoretical arrival times); 2) the differential P-wave amplitudes in terms of P-wave peak velocity) [reference] (which are computed using an existing P-peak motion prediction equation) and 3) the real-time estimation of back-azimuthal direction, measured shortly after the P-wave arrival. These three parameters are measured in real-time and are used as prior and conditional information to estimate the posterior probability of the event location parameters, e.g. the hypocenter coordinates and the origin time. The method is evolutive, since it updates the location parameters as new data are acquired by more and more distant stations as the P-wavefront propagates across the network. The output is a multi-dimensional Probability Density Function (PDF), which contains the complete information about the maximum likelihood parameter estimation with their uncertainty. The method is computationally efficient and optimized for running in real-time applications, where the earthquake location has to be retrieved in a very short time window (around 1 sec) after data acquisition. We tested the proposed strategy on a sequence of 29 earthquakes of the 2016-2017 central Italy seismic sequence acquired by the RAN (Rete Accelerometrica Nazionale) network with a magnitude range of 4.2-6.5. For the testing phase, we also simulated non-optimal conditions in terms of source-to-receiver geometry. Specifically, we tested the method by ssimulating the case of “offshore” earthquakes recorded by a coastal network and in the case of a linear “barrier-type” geometry of the network. Our approach turned out to be suitable to work in condition of a sparse network, with a limited number of nodes and poor azimuthal coverage. In most of the cases, reliable location errors, less than 10 km, are achieved within few seconds from the first recorded P wave. As compared to other classical location techniques (i.e RTLOC in PRESTo) our approach shows an improvement of the solutions, especially for the first instants (2 seconds after the first P-wave arrival at network) when a poor number of stations (less than 4) is available.

A fundamental feature of any Earthquake Early Warning System is the ability of rapidly broadcast earthquake information to a wide audience of potential end users and stakeholders, in an intuitive, customizable way. Smartphones and other mobile devices are nowadays continuously connected to the internet and represent the ideal tools for earthquake alerts dissemination, to inform a large number of users about the potential damaging shaking of an impending earthquake.Here we present a mobile App (named ISNet EWApp) for Android devices which can receive the alerts generated by a network-based Early Warning system. Specifically, the app receives the earthquake alerts generated by the PRESTo EWS, which is currently running on the accelerometric stations of the Irpinia Seismic Network (ISNet) in Southern Italy. In the absence of alerts, the EWApp displays the standard bulletin of seismic events occurred within the network. In the event of a relevant earthquake, instead, the app has a dedicated module to predict the expected ground shaking intensity and the available lead-time at the user position and to provide customized messages to inform the user about the proper reaction during the alert.We first present the architecture of both network-based system and EWApp, and then and describe its essential operational modes. The app is designed in a way that is easily exportable to any other network-based early warning system.

A coherence-based earthquake detection technique was applied to continuous (1 year) waveform data recorded along the Irpinia fault system (Southern Italy). The earthquake detection was performed using coherent P- and S-wave arrivals recorded by the dense seismic network operating in Irpinia and assuming a local velocity model. We applied a strategy to simultaneously detect and locate earthquakes and to discriminate among true and false detections using an automated and fast procedure, able to process 1 year of data in ~ 1.75 days. The final catalogue of automatically retrieved earthquakes shows a performance improvement with respect to the standard monitoring practices, with an increase in the number of detected small events of about a factor three with respect to the automatic Earth-worm Binder implemented in ISNet and decreases in completeness magnitude of almost half unit magnitude.

Since 2002 the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS) in Udine (Italy), the Agencija Republike Slovenije za Okolje (ARSO) in Ljubljana (Slovenia) and the Zentralanstalt fur Meteorologie und Geodynamik (ZAMG) in Vienna (Austria), are collecting, analyzing, archiving and exchanging seismic data in real time, initially in the framework of the EU Interreg IIIa Italia-Austria project “Trans-national seismological networks in the South-Eastern Alps”. As outcome of the successful cooperation, in the 2013 OGS, ARSO and ZAMG decided to officially merge their seismic monitoring efforts into the “Central and Eastern European Earthquake Research Network—CE3RN”. This work reports the results of a nine-month real-time test of the earthquake early warning (EEW) algorithm probabilistic and evolutionary early warning system carried out at the CE3RN. The study allowed identifying the actions to be implemented in order to let the CE3RN become in the next future an efficient cross-border EEW system.

The analysis of earthquake focal mechanisms provides information about the stress regime, fault geometry, and deformation processes acting in a given region. Generally, the techniques aimed at determining focal mechanism are designed to work in a specific magnitude range operating both in the time and frequency domain and using different data (e.g., P polarities, S ‐wave polarization, S / P ‐amplitude ratios, etc.). In this article, we present a new method, Bayesian inversion of spectral‐level ratios and P ‐wave polarities (BISTROP), that can be applied to both small and moderate‐to‐large magnitude events. BISTROP uses a Bayesian approach to jointly invert the long‐period spectral‐level P / S ratios and the P polarities to infer the fault‐plane solutions. We apply this method to analyze synthetic data as well as those generated by real earthquakes. We find that the obtained solutions for moderate earthquakes are comparable with those obtained using moment tensor inversion, and they are more constrained with respect to the solutions obtained using only P ‐polarity data for small earthquakes.

The monitoring of rock volume where offshore exploitation activities take place is crucial to assess the corresponding seismic hazard. Fluid injection/extraction operations generate a pore fluid pressure perturbation into the volume hosting the reservoir which, in turn, may trigger new failures and induce changes in the elastic properties of rocks. Our purpose is to evaluate the feasibility of reconstructing pore pressure perturbation diffusion in the host medium by imaging the 4D velocity changes using active seismic. We simulated repeated active offshore surveys and imaged the target volume. We constructed the velocity model perturbed by the fluid injection using physical modeling and evaluated under which conditions the repeated surveys could image the velocity changes. We found that the induced pressure perturbation causes seismic velocity variations ranging between 2–5% and 15–20%, depending on the different injection conditions and medium properties. So, in most cases, time-lapse tomography is very efficient in tracking the perturbation. The noise level characterizing the recording station sites is a crucial parameter. Since we evaluated the feasibility of the proposed 4D imaging strategy under different realistic environmental and operational conditions, our results can be directly applied to set up and configure the acquisition layout of surveys aimed at retrieving fluid-induced medium changes in the hosting medium. Moreover, our results can be considered as a useful starting point to design the guidelines to monitor exploitation areas.