Reliability of earthquake location procedures in heterogeneous areas: synthetic tests in the South Western Alps, Italy

Details Reliability of earthquake location procedures in heterogeneous areas: synthetic tests in the South Western Alps, Italy Reliability of earthquake location procedures in heterogeneous areas: synthetic tests in the South Western Alps, Italy

Apr 2001

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001pepi..123..247s&link_type=abstract

Physics of the Earth and Planetary Interiors, Volume 123, Issue 2-4, p. 247-266.

Physics

2

Scientific paper

The accuracy of procedures for locating earthquakes and tomographically imaging 3-D velocity structures, is influenced by factors such as network geometry, errors in picking seismic phases, modeling errors and velocity model uncertainties. The main purpose of this study is to investigate the importance of different error sources through synthetic experiments. The synthetic data sets were generated for a realistic 3-D velocity model of the South Western Alps adopting a precise raytracing technique. The actual station configuration and recorded seismicity during the passive seismological experiment Geofrance3D-Alps, conducted between August 1996 and February 1997, were used. The station configuration corresponded to an enhancement of the regional networks operating in the area, with the addition of temporary stations. In addition, synthetic data sets were corrupted by applying different error schemes. Furthermore, to assess the locating capabilities of the regional networks, synthetic data sets were constructed for synthetic events placed in correspondence to the nodes of a regular three dimensional (3-D) grid. We mimicked the actual data management scheme for synthetic data processing: we re-located the earthquakes, performed an inversion for a minimum 1-D velocity model with station corrections and, then, ran a complete 3-D velocity model inversion. One of the main results, confirming earlier studies was that earthquake locations in strongly heterogeneous areas, obtained using a regional 1-D model, can have significant errors. Even a minimum 1-D model with station corrections does not significantly improve the accuracy of parameter locations in the South Western Alps. For high precision locations, a 3-D model is needed. However, a 3-D model cannot be reconstructed from noise contaminated data recorded by a sparse regional network.

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