Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/8471
AuthorsStabile, T.* 
Iannaccone, G.* 
Zollo, A.* 
Lomax, A.* 
Ferulano, F.* 
Vetri, L.* 
Barzaghi, L.* 
TitleA comprehensive approach for evaluating network performance in surface and borehole seismic monitoring
Issue Date2012
Series/Report no./192(2013)
DOI10.1093/gji/ggs049
URIhttp://hdl.handle.net/2122/8471
KeywordsEarthquake ground motions
Computational seismology
Subject Classification04. Solid Earth::04.06. Seismology::04.06.10. Instruments and techniques 
AbstractThe accurate determination of locations and magnitudes of seismic events in a monitored region is important for many scientific, industrial and military studies and applications; for these purposes a wide variety of seismic networks are deployed throughout the world. It is crucial to know the performance of these networks not only in detecting and locating seismic events of different sizes throughout a specified source region, but also by evaluating their location errors as a function of the magnitude and source location. In this framework, we have developed a method for evaluating network performance in surface and borehole seismic monitoring. For a specified network geometry, station characteristics and a target monitoring volume, the method determines the lowest magnitude of events that the seismic network is able to detect (Mw detect), and locate (Mw loc) and estimates the expected location and origin time errors for a specified magnitude. Many of the features related to the seismic signal recorded at a single station are considered in this methodology, including characteristics of the seismic source, the instrument response, the ambient noise level, wave propagation in a layered, anelastic medium and uncertainties on waveform measures and the velocity model. We applied this method to two different network typologies: a local earthquake monitoring network, Irpinia Seismic Network (ISNet), installed along the Campania-Lucania Apennine chain in Southern Italy, and a hypothetic borehole network for monitoring microfractures induced during the hydrocarbon extraction process in an oil field. The method we present may be used to aid in enhancing existing networks and/or understanding their capabilities, such as for the ISNet case study, or to optimally design the network geometry in specific target regions, as for the borehole network example.
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