%0 Journal Article
%@ 0895-0695
%A Grigoli, Francesco
%A Cesca, Simone
%A Vassallo, M.
%A Dahm, Torsten
%A University of Potsdam, Institute of Earth and Environmental Sciences,Potsdam, Germany,
%A University of Potsdam, Institute of Earth and Environmental Sciences,Potsdam, Germany,
%A AMRA S.c.a.r.l., Analysis and Monitoring of Environmental Risk, Napoli, Italy,
%A University of Potsdam, Institute of Earth and Environmental Sciences,Potsdam, Germany,
%D 2013
%F epos:1744
%I Seismological Society of America
%J Seismological Research Letters
%N 4
%P 666-677
%T Automated Seismic Event Location by Travel-Time Stacking: An Application to Mining Induced Seismicity
%U https://episodesplatform.eu/eprints/1744/
%V 84
%X The automated location of seismic events is an important and challenging task in microseismic monitoring applications (e.g., to analyze induced seismicity following oil/geothermal field exploitation and mining operations), where we deal with a large number of seismic events and weak signals characterized by low signal‐to‐noise ratios. Given the large number of seismic events, manual location procedures are time consuming, or not feasible. Standard automated location routines require precise automated picking procedure and phases identification (Gharti et al., 2010). These methods are, generally, modified versions of the Geiger (1910, 1912) algorithm, based on the minimization of time residuals between theoretical and observed arrival times of body waves (generally first P and S onsets) by iterative inversion algorithms. In the last two decades a large number of picking algorithms have been developed; although P onsets can now be accurately picked, the automatic picking of later seismic phases (including S onsets) is still problematic. Their performance is limited in the presence of noisy data, when picking and phase identification might be difficult.