Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Monitoring the Microseismicity through a Dense Seismic Array and a Similarity Search Detection Technique: Application to the Gas-Storage Site of Collalto, North Italy

Antonio Scala
ORCID logo ,
Guido Maria Adinolfi
ORCID logo ,
Matteo Picozzi
* ORCID logo ,
Francesco Scotto di Uccio
ORCID logo ,
Gaetano Festa
ORCID logo ,
Grazia De Landro
,
Enrico Priolo
ORCID logo ,
Stefano Parolai
,
Rosario Riccio
,
Marco Romanelli
Version 1 : Received: 25 March 2022 / Approved: 28 March 2022 / Online: 28 March 2022 (11:12:18 CEST)

A peer-reviewed article of this Preprint also exists.

Scala, A.; Adinolfi, G.M.; Picozzi, M.; Scotto di Uccio, F.; Festa, G.; De Landro, G.; Priolo, E.; Parolai, S.; Riccio, R.; Romanelli, M. Monitoring the Microseismicity through a Dense Seismic Array and a Similarity Search Detection Technique: Application to the Seismic Monitoring of Collalto Gas-Storage, North Italy. Energies 2022, 15, 3504. Scala, A.; Adinolfi, G.M.; Picozzi, M.; Scotto di Uccio, F.; Festa, G.; De Landro, G.; Priolo, E.; Parolai, S.; Riccio, R.; Romanelli, M. Monitoring the Microseismicity through a Dense Seismic Array and a Similarity Search Detection Technique: Application to the Seismic Monitoring of Collalto Gas-Storage, North Italy. Energies 2022, 15, 3504.

Abstract

Seismic monitoring in areas where induced earthquakes could occur is a challenging topic for seismologists due to generally very low signal to noise ratio. Therefore, the seismological com-munity is devoting several efforts to the development of high-quality networks around the areas where fluid injection and storage and geothermal activities take place, also following the national induced seismicity monitoring guidelines. The use of advanced data-mining strategy, such as template matching filters, auto-similarity search and deep-learning approaches is recently further fostering such a monitoring enhancing the seismic catalogues and lowering the magnitude of completeness of these areas. In this framework, we carried out an experiment where a small-aperture seismic array was installed around the gas reservoir of Collalto, in North Italy. The continuous velocimetric data, acquired for 25 days, were analysed through the application of the optimized auto-similarity search technique FAST. The array was conceived as a cost-effective network, aimed at integrating, right above the gas storage site, the permanent high-resolution Collalto Seismic Network. The analysis allowed to detect micro-events down to magnitude Ml=-0.4 within a distance of ~15km from the array. Our results confirmed that the system based on the array installation and the FAST data-analysis might contribute to lower the magnitude of completeness around the site of about 0.7.

Keywords

Induced seismicity Monitoring; seismic arrays; sensor network technology; microearthquake detection

Subject

Environmental and Earth Sciences, Geophysics and Geology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0
Get PDF Cite Share 0
Bookmark BibSonomy Mendeley Reddit Delicious
×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.