Automatic seismic phase picking and consistent observation error assessment: application to the Italian seismicity

SUMMARY Accuracy of seismic phase observation and consistency of timing error assessment define the quality of seismic waves arrival times. High-quality and large data sets are prerequisites for seismic tomography to enhance the resolution of crustal and upper mantle structures. In this paper we present the application of an automated picking system to some 600 000 seismograms of local earthquakes routinely recorded and archived by the Italian national seismic network. The system defines an observation weighting scheme calibrated with a hand-picked data subset and mimics the picking by an expert seismologist. The strength of this automatic picking is that once it is tuned for observation quality assessment, consistency of arrival times is strongly improved and errors are independent of the amount of data to be picked. The application to the Italian local seismicity documents that it is possible to automatically compile a precise, homogeneous and large data set of local earthquake Pg and Pn arrivals with related polarities. We demonstrate that such a data set is suitable for high-precision earthquake location, focal mechanism determination and high-resolution seismic tomography.

[1]  N. Andersen,et al.  ON POWER ESTIMATION IN MAXIMUM ENTROPY SPECTRAL ANALYSIS , 1978 .

[2]  Charlotte A. Rowe,et al.  Automatic Phase Pick Refinement and Similar Event Association in Large Seismic Datasets , 2000 .

[3]  Zoltan A. Der,et al.  Automatic interpretation of regional short period seismic signals using CUSUM-SA algorithms , 2003 .

[4]  Claudio Chiarabba,et al.  A new view of Italian seismicity using 20 years of instrumental recordings , 2005 .

[5]  P. Shearer.  Application to the Whittier Narrows California aftershock sequence , 1997 .

[6]  Genshiro Kitagawa,et al.  Methods and Applications of Signal Processing in Seismic Network Operations , 2002 .

[7]  G. Selvaggi,et al.  Subcrustal earthquakes in the northern Apennines (Italy): Evidence for a still active subduction? , 1992 .

[8]  R. Lippitsch,et al.  Upper mantle structure beneath the Alpine orogen from high‐resolution teleseismic tomography , 2003 .

[9]  R. Fisher.  THE STATISTICAL UTILIZATION OF MULTIPLE MEASUREMENTS , 1938 .

[10]  Manfred Joswig,et al.  Automated reevaluation of local earthquake data by application of generic polarization patterns for P- and S-onsets , 1993 .

[11]  F. P. Lucente,et al.  Crustal and uppermost mantle structure in Italy fron the inversion of P-wave arrival times: geodynamic impliations , 1999 .

[12]  A. G. Lindh,et al.  Robust regional phase association , 1997 .

[13]  G. B. Cimini,et al.  Tomographic constraints on the geodynamic evolution of the Italian region , 1999 .

[14]  Genshiro Kitagawa,et al.  Multivariate time-series model to estimate the arrival times of S-waves , 1993 .

[15]  J. Jackson,et al.  The deep seismicity of the Tyrrhenian Sea , 1987 .

[16]  R. V. Allen,et al.  Automatic earthquake recognition and timing from single traces , 1978, Bulletin of the Seismological Society of America.

[17]  M. Leonard,et al.  Multi-component autoregressive techniques for the analysis of seismograms , 1999 .

[18]  A. F. Kushnir,et al.  Statistically optimal event detection using small array data , 1990, Bulletin of the Seismological Society of America.

[19]  Hengchang Dai,et al.  Automatic picking of seismic arrivals in local earthquake data using an artificial neural network , 1995 .

[20]  Manfred Baer,et al.  An automatic phase picker for local and teleseismic events , 1987 .

[21]  C. Chiarabba,et al.  Crustal velocity structure of the Apennines (Italy) from P-wave travel time tomography , 1996 .

[22]  Genshiro Kitagawa,et al.  A NEW EFFICIENT PROCEDURE FOR THE ESTIMATION OF ONSET TIMES OF SEISMIC WAVES , 1988 .

[23]  R. Shumway,et al.  Phase onset time estimation at regional distances using the CUSUM algorithm , 1999 .

[24]  Colin MacBeth,et al.  The application of back‐propagation neural network to automatic picking seismic arrivals from single‐component recordings , 1997 .

[25]  Christopher John Young,et al.  An Automatic, Adaptive Algorithm for Refining Phase Picks in Large Seismic Data Sets , 2002 .

[26]  Manfred Joswig,et al.  Master-event correlations of weak local earthquakes by dynamic waveform matching , 1993 .

[27]  A. Douglas,et al.  Bandpass filtering to reduce noise on seismograms: Is there a better way? , 1997, Bulletin of the Seismological Society of America.

[28]  R. V. Allen,et al.  Automatic phase pickers: Their present use and future prospects , 1982 .

[29]  G. Selvaggi,et al.  Crustal and deep seismicity in Italy (30 years after) , 1997 .

[30]  Reinoud Sleeman,et al.  Robust automatic P-phase picking: an on-line implementation in the analysis of broadband seismogram recordings , 1999 .

[31]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[32]  G. Selvaggi,et al.  Seismicity and P-wave velocity image of the Southern Tyrrhenian subduction zone , 1995 .

[33]  Peter Goldstein,et al.  85.5 SAC2000: Signal processing and analysis tools for seismologists and engineers , 2003 .

[34]  A. Clement,et al.  DIGITAL PROCESSING OF REFRACTION DATA STUDY OF FIRST ARRIVALS , 1972 .

[35]  Andrea Morelli,et al.  P wave tomography of the mantle under the Alpine-Mediterranean area , 2003 .

[36]  Gregory C. Beroza,et al.  Foreshock sequence of the 1992 Landers, California, earthquake and its implications for earthquake nucleation , 1995 .

[37]  Y. Morita,et al.  Automatic Detection of Onset Time of Seismic Waves and its Confidence Interval Using the Autoregressive Model Fitting , 1984 .

[38]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .