First application of ASDP software: a case study at Mt. Etna volcano and in the Acri region (Southern Italy)

Abstract

The PC-based automatic seismic data processing (ASDP) software module uses a multi-algorithm approach and a new procedure (MSA) for signal detection, phase grouping and event identification and location. It is designed for an efficient and accurate processing of local earthquakes records provided by single-site and array stations. Results from ASDP processing of two different data sets are analysed to evaluate its performance. By comparing of ASDP pickings with those revised manually the detection and subsequently the location capabilities of this software are assessed. The first data set is composed of 330 local microearthquakes (1.7⩽ M⩽3.8) recorded in the Mt. Etna volcano area by a telemetered analog seismic network. Digital data conversion of data is performed at the network centre operated by the Istituto Internazionale di Vulcanologia of C.N.R. The second data set comprises 40 ultra-microearthquakes (0.5⩽ M⩽2.0) recorded by a temporary array of four digital three-component stations, deployed in the Acri region (southern Calabria). For the Etnean earthquakes, a comparison of the automatic results with the manual picks indicates that the ASDP module can accurately pick 80% of the P-waves (differences are within 0.15 s) and 65% of the S-waves (differences are within 0.3 s). A peculiarity for these events is that the majority of the 3 three-component station records do not exhibit distinct S-waves. This statistics includes records with a strong noise (ground tremors and/or system electronic disturbances), but does not include false alarms due to non-seismic signals. Conversely, if we consider high-dynamic recordings of seismic digital data in a low-noise environment (Acri temporary array) the ASDP module can accurately pick 93% of the P-waves (differences with manual estimations are less than 0.1 s) and 87% of the S-waves (differences with manual estimations are less than 0.2 s). For this type of data with a favourable signal-to-noise ratio the automatic back-azimuths estimates are also extremely accurate in the 87% of the cases (differences estimations with those revised by an analyst and deriving from hypocenter solutions are generally within 10°). In general, our results indicate that both automatic ASDP and manual hypocenter locations are comparable within the estimated errors bounds. Furthermore, the comparison of ASDP automatic locations with those performed by XRTP-IASPEI software, routinely used for automatic locations at the Mt. Etna seismic network, indicates a better performance of the ASDP module.