ENI S.p.A. - E&P Division, San Donato Milanese (MI), Italy

The model developed by Aki and Chouet for the coda wave generation and propagation has been used to calculate the quality factor Q for the zone of the Aeolian Islands, southern Italy, in the frequency range of 1 to 12 Hz, and the scaling properties of the seismic spectrum in the magnitude range of 0.4 to 4.7. The Q found for the Aeolian area has a frequency dependence of the form Q = qf v. The absolute values of Q seem to be dependent on the station and location of the seismic events, confirming the strong lateral heterogeneities in the geological structure beneath the Aeolian Arc. A temporal variation has been noted in the Q calculated at Vulcano station (VPL) in a period of 3 weeks soon after the occurrence of a main shock of M, -- 5.5 located near the station. The scaling behavior of this sequence is similar to that obtained in two areas of California and one portion of Japan, with a corner frequency that remains constant with an increasing seismic moment between magnitudes 1 and 4. It differs substantially from the scaling properties of the Hawaian earthquakes that show a linear pattern, without an increase of the stress drop with magnitude. The fact that Vulcano is an active volcano seems not to influence the scaling properties of the seismic sequence localized very near it. It probably indicates that the aftershocks used for calculating the scaling law are generated out of the volcanic complex Lipari-Vulcano, in a zone with a good capability of accu- mulating the stress.

The 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.