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Discussion papers
https://doi.org/10.5194/essd-2019-113
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-113
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Data description paper 05 Jul 2019

Data description paper | 05 Jul 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

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

Tony Alfredo Stabile1, Vincenzo Serlenga1, Claudio Satriano2, Marco Romanelli3, Erwan Gueguen1, Maria Rosaria Gallipoli1, Ermann Ripepi1, Jean-Marie Saurel2, Serena Panebianco1,4, Jessica Bellanova1, and Enrico Priolo3 Tony Alfredo Stabile et al.
  • 1Istituto di Metodologie per l’Analisi Ambientale,Consiglio Nazionale delle Ricerche, Tito(PZ), 85050, Italy
  • 2Institut de Physique du Globe de Paris, Paris, 75005, France
  • 3Centro di Ricerche Sismologiche, Istituto nazionale di oceanografia edi geofisica sperimentale, Sgonico(TS), 34010, Italy
  • 4Università degli Studi della Basilicata, Dipartimento di Scienze, Potenza(PZ), 85100, Italy

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; (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 nucleation 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 by 8 stations deployed in an area of 17 km x 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 to detect induced microearthquakes, local/regional earthquakes, and teleseisms 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 (2019-03-23) are already released with open-access policy through the FDSN webservices and are available from http://www.fdsn.org/networks/detail/3F_2016 (https://doi.org/10.7914/SN/3F_2016; Stabile et al., 2016).

Tony Alfredo Stabile et al.
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Tony Alfredo Stabile et al.
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3F (2016-2019): SIR-MIUR Project INSIEME - broadband seismic network in Val d'Agri (southern Italy) T. A. Stabile and the INSIEME Team https://doi.org/10.7914/SN/3F_2016

Tony Alfredo Stabile et al.
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Short summary
This paper presents data collected by a seismic network developed in the framework of the INISIEME project aimed to study induced seismicity processes. The network is composed by 8 stations deployed around two clusters of induced microearthquakes in the High Agri Valley (southern Italy). The solutions for reducing the background noise level are presented and the quality of acquired data are discussed. Such open-access data can be used by the scientific community for different applications.
This paper presents data collected by a seismic network developed in the framework of the...
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