The INSIEME seismic network: a research infrastructure for studying induced seismicity in the High Agri Valley (southern Italy)

Abstract

Abstract. 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 Mw=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 17 km×11 km 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.

Analysis of the 2016–2018 fluid-injection induced seismicity in the High Agri Valley (Southern Italy) from improved detections using template matching

“…The detection of events was performed by cross-correlating 8 master events (see Supplementary Table S1 online) and continuous data acquired by INS1 station, the nearest station to the analyzed seismicity cluster (see Fig. 1 ) and the only one installed in a borehole at a depth of 50 m (the others are at 6 m depth), equipped with a 120 s–100 Hz broadband sensor which provides good quality data with low background noise level 18 . In comparison with INS1, the other stations provide disproportionally low signal-to-noise ratio (SNR) of seismic arrivals and do not provide a reliable way of detecting weak events.…”

“…The nearest station to the analyzed seismicity cluster (INS1 station, see Fig. 1 ) of the INSIEME seismic network 18 was used for detection and the eight different master events reported in Supplementary Table S1 were selected to automatically detect weaker signals with high similarity of waveforms. Supplementary Fig.…”

“…Furthermore, from 2018-04-14 to 2018-06-29 the station INS1 suffered a significant disturbance in the seismic signal together with several switch offs due to a current instability. Possible recurrence of this problem was prevented by connecting this station to a power system based on solar panels and batteries 18 . Only in this switch off period the single-station template matching algorithm was applied additionally to the continuous data stream of station INS3, allowing the detection of further 21 events.…”

“…The deployment of high-density microseismic monitoring networks has been demonstrated to be a powerful approach to improve the detection performance of weak events 11 – 18 . In addition to the high density of stations, the main advantages of modern microseismic monitoring networks are: (1) the use of high quality sensors with a large dynamic range placed in shallow or deep boreholes which reduces the background noise level 18 – 20 ; (2) the availability of continuous data streams from each seismic station allowing for the real-time or off-line application of advanced detection 21 – 23 and location 24 – 30 techniques, which results in decreased magnitude of completeness and generation of massive microseismic catalogues of accurate located events.…”

“…The fluid-induced microseismicity has been identified and studied for the period ranging from 2006 to 2012–2014 by different authors 38 – 43 who used triggered data of the seismic network deployed in the study area since July 2001 by the Eni oil company which is managing the Val d’Agri oil filed 44 . In 2016 the INSIEME temporary seismic network 45 was deployed in the area to study induced seismicity in the framework of the INSIEME project of the Italian SIR-MIUR programme 18 , providing continuous data streams from 8 surface borehole stations. Since 2016 these data allow the detection and location of weak events that were not included neither in the Italian National Seismic Network, nor in the Eni oil company seismic catalogues.…”