The waveform similarity approach to identify dependent events in instrumental seismic catalogues

SUMMARY In this paper, waveform similarity analysis is adapted and implemented in a declustering procedure to identify foreshocks and aftershocks, to obtain instrumental catalogues that are cleaned of dependent events and to perform an independent check of the results of traditional declustering techniques. Unlike other traditional declustering methods (i.e. windowing techniques), the application of cross-correlation analysis allows definition of groups of dependent events (multiplets) characterized by similar location, fault mechanism and propagation pattern. In this way the chain of intervening related events is led by the seismogenetic features of earthquakes. Furthermore, a time-selection criterion is used to define time-independent seismic episodes eventually joined (on the basis of waveform similarity) into a single multiplet. The results, obtained applying our procedure to a test data set, show that the declustered catalogue is drawn by the Poisson distribution with a degree of confidence higher than using the Gardner and Knopoff method. The declustered catalogues, applying these two approaches, are similar with respect to the frequency‐magnitude distribution and the number of earthquakes. Nevertheless, the application of our approach leads to declustered catalogues properly related to the seismotectonic background and the reology of the investigated area and the success of the procedure is ensured by the independence of the results on estimated location errors of the events collected in the raw catalogue.

[1]  D. L. Anderson,et al.  Theoretical Basis of Some Empirical Relations in Seismology by Hiroo Kanamori And , 1975 .

[2]  L. Knopoff,et al.  Bursts of aftershocks, long-term precursors of strong earthquakes , 1980, Nature.

[3]  P. Reasenberg,et al.  Earthquake Hazard After a Mainshock in California , 1989, Science.

[4]  F. Waldhauser,et al.  Slip‐parallel seismic lineations on the Northern Hayward Fault, California , 1999 .

[5]  Polona Zupančič,et al.  Probabilistic Seismic Hazard Assessment Methodology for Distributed Seismicity , 2003 .

[6]  Ömer Alptekin,et al.  Effect of Aftershocks on Earthquake Hazard Estimation: An Example from the North Anatolian Fault Zone , 1999 .

[7]  Gregory C. Beroza,et al.  High‐resolution image of Calaveras Fault seismicity , 2002 .

[8]  D. Depolo,et al.  Foreshock probabilities in the western Great-Basin eastern Sierra Nevada , 1993 .

[9]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[10]  P. Reasenberg.  Second‐order moment of central California seismicity, 1969–1982 , 1985 .

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

[12]  Richard C. Aster,et al.  Comprehensive characterization of waveform similarity in microearthquake data sets , 1993, Bulletin of the Seismological Society of America.

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

[14]  R. Di Giovambattista,et al.  Local earthquake relative location by digital records , 1987 .

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

[16]  William L. Ellsworth,et al.  Monitoring velocity variations in the crust using earthquake doublets: An application to the Calaveras Fault, California , 1984 .

[17]  Marco Cattaneo,et al.  Reconstruction of seismogenetic structures by multiplet analysis: An example of Western Liguria, Italy , 1997, Bulletin of the Seismological Society of America.

[18]  P. Augliera,et al.  A Waveform Similarity Approach to Investigate Seismicity Patterns , 1999 .

[19]  Elena Eva,et al.  Detection of earthquake clusters on the basis of waveform similarity: An application in the monferrato region (Piedmont, Italy) , 2006 .

[20]  Fred W. Klein,et al.  Deep fault plane geometry inferred from multiplet relative relocation beneath the south flank of Kilauea , 1994 .

[21]  F. Waldhauser,et al.  Optimizing Correlation Techniques for Improved Earthquake Location , 2004 .

[22]  F. Waldhauser,et al.  A Double-Difference Earthquake Location Algorithm: Method and Application to the Northern Hayward Fault, California , 2000 .

[23]  L. Knopoff,et al.  Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian? , 1974, Bulletin of the Seismological Society of America.

[24]  Stefano Solarino,et al.  An Improved Method for the Recognition of Seismic Families: Application to the Garfagnana–Lunigiana Area, Italy , 2005 .

[25]  Masaru Tsujiura,et al.  Characteristic frequencies for earthquake families and their tectonic implications: Evidence from earthquake swarms in the kanto district, Japan , 1983 .

[26]  C. Cornell.  Engineering seismic risk analysis , 1968 .

[27]  Nicholas Deichmann,et al.  Rupture geometry from high-precision relative hypocentre locations of microearthquake clusters , 1992 .

[28]  Stephen D. Malone,et al.  High precision relative locations of earthquakes at Mount St. Helens, Washington , 1987 .

[29]  H. Langer,et al.  High-Precision Relative Locations of Two Microearthquake Clusters in Southeastern Sicily, Italy , 2003 .

[30]  A. Frankel.  Mapping Seismic Hazard in the Central and Eastern United States , 1995 .

[31]  William H. Press,et al.  Numerical Recipes in FORTRAN - The Art of Scientific Computing, 2nd Edition , 1987 .

[32]  Leon Knopoff,et al.  The statistics of earthquakes in Southern California , 1964 .

[33]  R. Geller,et al.  Four similar earthquakes in central California , 1980 .

[34]  David A. Rhoades,et al.  Båth's law and the self‐similarity of earthquakes , 2003 .

[35]  Marco Cattaneo,et al.  Seismic multiplets analysis and its implication in seismotectonics , 1995 .

[36]  Hansruedi Maurer,et al.  Microearthquake cluster detection based on waveform similarities, with an application to the western Swiss Alps , 1995 .

[37]  Cataldo Godano,et al.  Mdtifractal analysis of earthquake catalogues , 1995 .

[38]  Patrizia Tosi,et al.  Scaling properties of the spatio-temporal distribution of earthquakes: a multifractal approach applied to a Californian catalogue , 1999 .

[39]  Stefano Solarino,et al.  Seismicity of Garfagnana-Lunigiana (Tuscany, Italy) as recorded by a network of semi-broad-band instruments , 2002 .