In this paper, we examined the dynamical properties of the fluid-injection microseismicity at the Val d'Agri oil field (southern Italy) by applying different statistical methods to find correlations and common periodicities with injection parameters, such as injected volumes and injection pressure. Two periods of observation were analyzed: (1) from 2006 to 2015 (the first 10 years after the beginning of injection operations), the seismicity was recorded by the seismic network of the ENI company that manages the exploitation of the oilfield; (2) from 2016 to 2018, the seismicity was recorded by a denser seismic network capable of significantly reducing the completeness magnitude. If a significant correlation between seismicity and fluid-injection variables was found in the first period, in the second period, the seismic activity and injection variables were characterized by common periodicities after the reservoir acidification and for injection rates above 1900 m3/day. Finally, we applied and compared two different approaches proposed in the literature to forecast the maximum expected magnitude. The results showed that one of the approaches yielded an estimated maximum magnitude of Mmax = 1.7 +/- 0.4, which is consistent with the maximum observed magnitude.

A methodological approach based on the integration of different survey techniques may be particularly suitable for the study of areas with complex geology such as those affected by landslide phenomena. The results obtained by the application of combined electrical resistivity tomography (ERT) technique, ambient seismic noise mea-surements (single station and array), geological investigation and granulometric analysis to characterize and study a landslide occurred on December 3rd, 2013 in Basilicata region (southern Italy) are presented and dis-cussed. The landslide partially affected the peri-urban area of Montescaglioso town and caused damages to small -medium enterprises, infrastructures, and housing. The analysis of ambient noise signals made possible to esti-mate the depth of the contacts between the main geological formations outcropping in the area and revealed the existence of directional resonance effects. The discontinuities observed by the ERT have confirmed the presence of different lithotypes and allowed illuminating the sliding surface at a depth of about 40 m in agreement with the seismic results and boreholes data. The shallow discontinuities inferred from geophysical surveys were supported also by the results of a detailed granulometric analysis performed on a geognostic survey, confirming the presence of a heterogeneous sedimentary deposit in the area. In such complex context, the acquisition of spatially distributed geophysical properties permitted to increase the knowledge of the geological setting of the area, reaching a level of detail that cannot be observed by applying only a sparse discrete direct sampling. The integration of all the obtained information allowed the delineation of geophysical discontinuities related to the presence of sliding or weakness surfaces and areas with high water content that could contribute to future activation of the movement. This information was crucial to better understand the nature of the landslide, contributing to the planning and the implementation of risk mitigation actions and to the design of remediation works.

The accurate characterization of microearthquake sequences allows seismologists to better understand the physical processes involved in earthquake nucleation and rupture propagation and to gain insights on fault geometry at depth. Standard procedures for seismic sequences analysis are based on manual detection and phase-picking, requiring a huge amount of work from expert seismologists, particularly in the case of microseismic events. Here we show how the investigation of a low-magnitude foreshock-mainshock-aftershock sequence, occurred in August 2020 close to Castelsaraceno village (southern Italy), greatly benefited from the application of a semi-automated template matching and machine-learning based workflow. The phase-picking was automatically performed through a deep-learning algorithm on 202 microearthquakes detected between July and October 2020, followed by an automatic multi-step absolute and relative earthquake location procedure. The 72 relocated events of the seismic sequence were clustered in time (7-12 August) and in a narrow range of depths (10-12 km). The Ml 2.1 foreshock doublet and the Ml 2.9 mainshock identified a persistent asperity. The joint analysis of aftershocks distribution, the mainshock focal mechanism, and the geology of the study area suggest the occurrence of the sequence along a NNE-SSW left-lateral, transtensional fault in the brittle portion of the crystalline basement.

We investigate the spatiotemporal evolution of ground motion caused by reservoir-induced seismicity at the Pertusillo artificial lake in southern Italy. The area has a strong seismogenic potential, having been affected in the past by the 1857, Mw 7.0 Basilicata earthquake. We consider ~1,000 microearthquakes that occurred from 2001 to 2018 and were recorded by a local network of nine seismic stations. The ground motion intensity associated with microseismicity allows us to identify two periods, each lasting approximately 2 years. They are characterized by a high rate of events but exhibit different source properties and spatial distributions. In the first period, the seismicity is spatially clustered close to the lake, on faults with different orientations and kinematics. In the second period, the seismicity is distributed along the Monti della Maddalena faults. Comparing the ground motion intensities of the two periods, we observe that events that occurred in the first period are associated with higher stress levels than others, in agreement with the b-values of the respective frequency-magnitude distributions. We compare the temporal evolution of the ground motion intensity with the rainfall and water levels measured at the artificial lake, as well as with the discharge of a ~80 km distant spring, which is strictly controlled by climate trends. The results provide information about the regional processes acting on the southern Apennines. Our results show that the microseismicity is clearly associated with the Pertusillo artificial lake in the first period, whereas in the second period is a result of a combination of local effects due to water table oscillations of the lake itself, regional tectonics, and the poroelastic and elastic phenomena associated with carbonate rocks hosting aquifers.

Deep fluids play active roles during the preparatory phases of large earthquakes and, through their chemical signature, carry information about deep processes within the seismogenic crust. Due to its inertness and isotopic signature, helium (the lightest noble gas) is a useful tracer for investigating the processes of storage and transfer of fluids through the crust, including those prior to hazardous earthquakes. Here we analyse a 12-year earthquake catalogue from the Irpinia Fault Zone, Italy, to compute the 4He outputs from the seismogenetic fault zones (from 104 to 106mol y-1 with an annual tenfold variability) and compare these with estimates of long-term helium flux. We find that low-magnitude earthquakes (M < 4) efficiently contribute to variations of the crustal helium output into the atmosphere which supports the impulsive nature of He degassing in tectonically active continental regions. We conclude that there is a quantitative relationship between crustal helium outputs and the volume of fault zones, and suggest variations in helium flux may represent a gauge of changes in the stress field that are related to the nucleation of earthquakes.

This work proposes a method for estimating and compensating the atmospheric phase screen (APS) in sets of synthetic aperture radar (SAR) interferograms generated with a ground-based SAR (GB-SAR) instrument. We address the presented approach's physical, statistical, and mathematical framework by discussing its potential and limitations. In contrast with other existing algorithms that estimate the APS from the unwrapped phase signals, our methodology is based on the straightforward analysis of the wrapped phases, directly. Therefore, the method is not affected by any potential phase unwrapping mistake, and it is suitable for multitemporal interferometric SAR (InSAR) applications. The effects of the local topography, the decorrelation noise, and the ground deformation on the APS estimates are deeply studied. Experiments performed on simulated and real GB-SAR InSAR data corroborate the validity of the theory. In particular, the simulated results show that the method is beneficial in zones with medium-to-high topographic slopes (e.g., for Alpine and mountainous regions).

We applied an integrated, non-invasive and non-destructive seismic and electromagnetic sensing for understanding the static and dynamic properties of the Gravina bridge and its interaction with foundation soils. The 'Gravina' is a bow-string bridge located in the city of Matera (Southern Italy) that extends for 144 m along a steel-concrete deck. For foundation soils characterization we executed 3 high-resolution geo-electrical tomographies, 1 bi-dimensional seismic array and two single station seismic noise measurements. The main structural characteristics of the bridge were evaluated through seismic and electromagnetic sensing. The seismic sensing was carried out with four accelerometers and twelve velocimeters (standard and low cost sensors) installed with different geometrical arrangement for real-time and on-demand ambient noise recordings, vibration tests and earthquake recordings. The electromagnetic data have been collected by placing the IBIS-S system below the deck of the bridge. Acquired data have been analyzed in frequency domain with the aim to evaluate the eigenfrequencies and equivalent viscous damping factors.

Tropospheric excess path delays afflict surface motion measurements when Ground-based SAR (GB-SAR) interferometry is adopted. In this work, we propose an adaptive frequency-domain methodology to estimate the atmospheric phase screen (APS) components using wrapped GB-SAR interferometric data pairs, thus avoiding any possible phase unwrapping mistake. The experimental results show that the developed technique can detect and compensate for tropospheric fluctuations found in steep mountain areas without using any external digital elevation model of the investigated area. The paper addresses the potential of the developed technique by applying it on a set of simulated data.

An integrated geophysical approach using non-invasive, non-destructive, and cost-effective seismic and electromagnetic techniques has been implemented to recognize the static and dynamic properties (i.e. eigenfrequencies, equivalent viscous damping factors, and related modal shapes) of the Gravina Bridge and its interaction with foundation soils. The "Gravina" is a bow-string bridge located on outcropping calcarenites in the city of Matera (Southern Italy) and develops for 144 m along a steel-concrete deck. The foundation soil characteristics have been evaluated by means of three high-resolution geo-electrical tomographies, one Vs velocity profile, and two site amplification functions. The main structural characteristics of the bridge have been estimated through permanent and on-demand monitoring using seismic and electromagnetic sensing. The former consisted of accelerometers and velocimeters installed with different geometrical arrangements for permanent earthquake and on-demand ambient vibration test recordings. The electromagnetic sensing was realized by a microwave radar interferometer placed below the deck to measure the displacements of the whole scenario illuminated by the antenna beam providing a continuous mapping of the static and dynamic displacements of the entire target. Acquired data have been analyzed in both frequency and time-frequency domain with the aim to study the stationary and non-stationary response of the monitored bridge. These experimental campaigns allowed us to assess the robustness of the proposed approach and to set up the zero-time reference point of the bridge dynamic parameters.

Improving the capability of seismic network to detect weak seismic events is one of the timeless challenges in seismology: the greater is the number of detected and locatable seismic events, the greater insights on the mechanisms responsible for seismic activation may be gained. Here we implement and apply a single-station template matching algorithm to detect events belonging to the fluid-injection induced seismicity cluster located in the High Agri Valley, Southern Italy, using the continuous seismic data stream of the closest station of the INSIEME network. To take into account the diversity of waveforms, albeit belonging to the same seismic cluster, eight different master templates were adopted. Afterwards, using all the stations of the network, we provide a seismic catalogue consisting of 196 located earthquakes, in the magnitude range - 1.2 <= Ml <= 1.2, with a completeness magnitude Mc = - 0.5 ± 0.1. This rich seismic catalogue allows us to describe the damage zone of a SW dipping fault, characterized by a variety of fractures critically stressed in the dip range between ~ 45° and ~ 75°. The time-evolution of seismicity clearly shows seismic swarm distribution characteristics with many events of similar magnitude, and the seismicity well correlates with injection operational parameters (i.e. injected volumes and injection pressures).

We present an electrical resistivity model obtained from a 2D Magnetotelluric survey across a large sector of the Southern Apennine in the High Agri Valley (HAV), a NW-SE trending intra-mountain basin, with a high seismogenic potential. The intensive hydrocarbon exploitation (Val d'Agri oilfield) makes this area also affected by induced seismicity. In this HAV sector, the injection of salt-water in an unproductive disposal well (Costa Molina 2) causes localized swarms of microearthquakes; a second cluster of continuous induced seismicity is also observed SW of the Pertusillo Lake and it is associated to the seasonal fluctuations of the reservoir's water level. The major insight inferred from this study concerns a better understanding of the geological and tectonic framework in the HAV. The electrical resistivity model images the subsurface as conductive sedimentary sequences (Allochthonous Units) upon the carbonate Apulian Platform Unit characterized by higher resistivity values. Both these units appear composed of thrust-and-fold system deepening with larger wavelength anticlines N-E toward. Most of the structures identified in the magnetotelluric model are rather superficial and confined within the Allochthonous Units. A sudden break of the Apulian platform under the central part of the MT profile defines a conductive zone possibly associated to a major SW-dipping reverse fault or to several branches, as closely spaced thrust-sheets cutting eastern flanks of the Agri Valley. Additional information on the HAV deep structures comes from the joint interpretation of the resistivity model and a 3D seismic tomographic model obtained from the inversion of passive seismic data collected in the period 2002-2018. The availability of this elastic representation of the subsurface allowed us to perform a cluster analysis on the electrical resistivity and seismic P-wave velocity distribution within the subsoil. This joint quantitative interpretation unveiled new insights, otherwise hidden by individual models, on the subsurface structure distinguishing some rheological zones in terms of barriers and asperities.

This study discusses the effect of buildings vibrations in the urban field in the context of local seismic response studies in order to evaluate the possible occurrence of double resonance effects during strong-motions. The aim is to recognise the interaction effect between near surface geology and all overlying buildings in the urban area of the city of Matera (southern Italy). Single station seismic ambient noise measurements (230) were performed on the main lythologies (134) and on the principal building typologies (96). Soil and building measurements allowed estimating the main frequencies and relative amplitudes of the soil fundamental peaks as well as the first vibrational frequency of buildings. The period-height linear relationship, derived by experimental results, made it possible estimating the fundamental frequency for all the Matera's buildings. Having also estimated the frequencies at each point of the urban soil it was thus possible to obtain a soil-building resonance map in the linear elastic domain. Matera represents an important case study because the first vibration frequency for most of the buildings is quite close to those of the foundation soils. About 21% of buildings show high probability of occurrence of soil-building resonance effect, about 63% of the buildings are characterised by a medium resonance level, while about 16% are at zero or very low level. The proposed approach makes it also possible to identify the areas of the city characterised by these different probabilities of resonance levels.

In this article, a framework of building monitoring is developed and transient and permanent variations of the fundamental period of vibration caused by both damage and repair interventions are investigated. The buildings of the University of Ferrara (Emilia-Romagna Region, Northern Italy), struck by the 2012 Emilia seismic sequence, were monitored using both temporary and permanent equipment: the first one to perform ambient vibration tests and the second one to implement permanent real-time monitoring for earthquake recording. Three on-demand ambient vibration tests were performed at each floor of the buildings: the first dataset was acquired a few months before the mainshock occurred on 20 May 2012 (M-L = 5.9, 6.8 km depth and 30 km epicentral distance); the second was acquired right after the end of the sequence, when the building showed slight damage (degree 1 according to the European Macroseismic Scale 98); finally, the third dataset was acquired in 2016 after the repair intervention. The data analysis clearly documented the permanent drop of the first vibration frequency as a symptom of the damage and its partial recovery that followed the repairs. The permanent real-time monitoring system, despite the fact that it was implemented using low-cost sensors, provided an insight into the intra-event frequency variation, allowing in turn a preliminary damage assessment.

The High Agri Valley is a tectonically active area in southern Italy characterized by high seismic hazard related to fault systems capable of generating up to M = 7 earthquakes (i.e. the 1857 M-w = 7 Basilicata earthquake). In addition to the natural seismicity, two different clusters of induced microseismicity were recognized to be caused by industrial operations carried out in the area: (1) the water loading and unloading operations in the Pertusillo artificial reservoir and (2) the wastewater disposal at the Costa Molina 2 injection well. The twofold nature of the recorded seismicity in the High Agri Valley makes it an ideal study area to deepen the understanding of driving processes of both natural and anthropogenic earthquakes and to improve the current methodologies for the discrimination between natural and induced seismic events by collecting high-quality seismic data. Here we present the dataset gathered by the INSIEME seismic network that was installed in the High Agri Valley within the SIR-MIUR research project INSIEME (INduced Seismicity in Italy: Estimation, Monitoring, and sEismic risk mitigation). The seismic network was planned with the aim to study the two induced seismicity clusters and to collect a full range of open-access data to be shared with the whole scientific community. The seismic network is composed of eight stations deployed in an area of 17km x 11km around the two clusters of induced microearthquakes, and it is equipped with triaxial weak-motion broadband sensors placed at different depths down to 50 m. It allows us to detect induced microearthquakes, local and regional earthquakes, and teleseismic events from continuous data streams transmitted in real time to the CNR-IMAA Data Centre. The network has been registered at the International Federation of Digital Seismograph Networks (FDSN) with code 3F. Data collected until the end of the INSIEME project (23 March 2019) are already released with open-access policy through the FDSN web services and are available from IRIS DMC (https://doi.org/10.7914/SN/3F_2016; Stabile and INSIEME Team, 2016). Data collected after the project will be available with the permanent network code VD (https://doi.org/10.7914/SN/VD, CNR IMAA Consiglio Nazionale delle Ricerche, 2019) as part of the High Agri Valley geophysical Observatory (HAVO), a multi-parametric network managed by the CNR-IMAA research institute.

In August 2016, a magnitude 6.0 earthquake struck Central Italy, starting a devastating seismic sequence, aggravated by other two events of magnitude 5.9 and 6.5, respectively. After the frst mainshock, four Italian institutions installed a dense temporary network of 50 seismic stations in an area of 260 km2. The network was registered in the International Federation of Digital Seismograph Networks with the code 3A and quoted with a Digital Object Identifer (https://doi.org/10.13127/SD/ ku7Xm12Yy9). Raw data were converted into the standard binary miniSEED format, and organized in a structured archive. Then, data quality and completeness were checked, and all the relevant information was used for creating the metadata volumes. Finally, the 99Gb of continuous seismic data and metadata were uploaded into the INGV node of the European Integrated Data Archive repository. Their use was regulated by a Memorandum of Understanding between the institutions. After an embargo period, the data are now available for many different seismological studies.

Local earthquake tomography allows to both image the subsurface elastic properties of an area and to locate earthquakes. In this work, we discuss the choice of best parameterization in a tomographic model and the influence of retrieved velocity models on the accuracy of earthquake location in the High Agri Valley, southern Italy. The tomographic inversions were carried out with two datasets (dataset A and dataset B). Dataset B was obtained by integrating in the dataset A the data recorded by a very dense seismic network deployed around a specific cluster of seismicity. Velocity models obtained from the inversion of the two datasets are characterized by the same parameterization. However, the anomalies retrieved by the inversion of the second dataset look more reliable, based on results of checkerboard test. The retrieved 3D velocity model contributed to improve the accuracy of earthquake locations with respect to the 1D model. Data recorded by a very dense network in dataset B further contributed to reduce the errors and to improve the clustering of hypocentral positions of the best azimuthally covered cluster of seismicity. The importance of a 3D velocity model and of a proper network geometry for earthquake location is therefore demonstrated.

The increasingly intensive use of natural resources with consequent environmental impacts has generated numerous social conflicts over the years, for whose solution it is necessary to build up an innovative territorial governance model based on sustainable and resilience thinking. At the international level, the problems associated with oil and gas extraction activities have been tackled by recognizing scientific research as a strategic role aimed at guaranteeing a more in-depth knowledge of environmental issues, the creation of collaboration networks between the various stakeholders and the whole usability of environmental data. This article presents the commitment made by the National Research Council of Italy - Institute of Methodologies for Environmental Analysis - CNR-IMAA to make the Val d'Agri community, an area affected by mining activities, less vulnerable and more resilient. Through the combined use of different scientific research methodologies, a multidisciplinary approach was developed which contributed to increasing the overall knowledge of the environmental problems of Val d'Agri as well as providing concrete indications for the development of more effective territorial management tools. Other activities, complementary to those of research, were aimed at ensuring correct and detailed environmental data information and communication and a broaden participation and involvement of citizens.

A geophysical approach, based on the integration of satellite differential interferometric SAR technique and in situ geoelectrical and seismic methods, was applied with the aim to characterize a portion of urban area of Avigliano (PZ) town in Basilicata Region (southern Italy) affected by ground instability phenomena. Satellite analysis helped to discriminate areas of the town affected by superficial deformations and to monitor the dynamic behaviour of the structures located in these areas. Results from geoelectrical and seismic (active and passive) methods were compared with direct data (stratigraphic) and were interpreted with the aim to reconstruct the geometry of the subsoil. The joint application of both in situ techniques allowed the overcoming of the specific limits of each method and to improve the poor quality of the data due to the noise conditions typical of measurements carried out in urban areas. A preliminary geophysical model of the subsoil was obtained. The geophysical contrasts highlighted the presence of lithological discontinuities due to the superficial deformation processes that are affecting the portion of the investigated urban area. All the information has been transferred to the public administration technicians involved in the mitigation of hydrogeological risk in Basilicata Region.

After the ML = 6.0 earthquake which occurred on 24th August 2016 in central Italy, some unexpected variability in the damage distribution were identified in many villages located around the epicentral area. In particular, despite a distance of only about 1300 m, the villages of Pescara del Tronto and Vezzano (both districts in the Arquata del Tronto municipality) had a different damage assessment. Pescara del Tronto suffered heavy damage, with many collapsed masonry buildings and 48 fatalities, whereas Vezzano suffered negligible to slight damage to a few buildings. This paper provides vulnerability and damage assessment in order to detect potential significant differences in the building vulnerability and damage level. Geophysical prospectings were performed to assess whether site effects could have increased the damage in Pescara del Tronto compared to Vezzano.