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

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 differ ent data sets are analysed to evaluate its performance. By comparing of ASD P pickings with those revised manually the detection and subsequently the l ocation capabilities of this software are assessed. The first data set is c omposed of 330 local microearthquakes (1.7 less than or equal to M less tha n or equal to 3.8) recorded in the Mt. Etna volcano area by a telemetered a nalog 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,less tha n or equal to M less than or equal to 2.0) recorded by a temporary array of four digital three-component stations, deployed in the Acri region (southe rn Calabria). For the Etnean earthquakes, a comparison of the automatic res ults with the manual picks indicates that the ASDP module can accurately pi ck 80% of the P-waves (differences are within 0.15 s) and 65% of the S-wave s (differences are within 0.3 a). A peculiarity for these events is that th e majority of the 3 three-component station records do not exhibit distinct S-waves. This statistics includes records with a strong noise (ground trem ors and/or system electronic disturbances), but does not include false alar ms due to non-seismic signals. Conversely, if we consider high-dynamic reco rdings of seismic digital data in a low-noise environment (Acri temporary a rray) the ASDP module can accurately pick 93% of the P-waves (differences w ith manual estimations are less than 0.1 s) and 87% of the S-waves (differe nces with manual estimations are less than 0.2 s). For this type of data wi th a favourable signal-to-noise ratio the automatic back-azimuths estimates are also extremely accurate in the 87% of the cases (differences estimatio ns with those revised by an analyst and deriving from hypocenter solutions are generally within 10 degrees). In general, our results indicate that bot h automatic ASDP and manual hypocenter locations are comparable within the estimated errors bounds. Furthermore, the comparison of ASDP automatic loca tions with those performed by XRTP-IASPEI software, routinely used for auto matic locations at the Mt. Etna seismic network, indicates a better perform ance of the ASDP module. (C) 1999 Elsevier Science B.V. All lights reserved .