Automated identification and timing of crustal phases for tomographic studies and applications to the Marmara region in NW Turkey

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Precise knowledge of the 3D-velocity structure is an important pre-requisite when aiming at tectonically characterizing target regions using high-precision earthquake hypocenter locations. In that respect, precise phase arrival times selected from extensive waveform data archives are the most important input parameter. The aim of this project is to develop algorithms for automated identification and accurate timing of crustal phases and their inversion to derive a three-dimensional velocity model of the broader Marmara region in NW Turkey. Based on recent developments of automated P- and S-phase picking algorithms it is planned to extend and apply these algorithms to additional crustal and uppermost mantle phases such as Pg, Pn, PmP, and its S-wave pendants. Based on recent results, we will make use of statistical modeling, multivariate time series analysis, and heuristic methodologies. The new approach should also provide reliable, non-discrete and non-symmetrical error estimates of the derived phase-onset times. Arrival times of distinct identified phase onsets will serve as input for non-linear location methods like NonLinLoc and VELEST to establish a minimum 1D-velocity model, which will then serve as a starting model for the 3D-inversion using SIMULPS14. The newly developed algorithms will be applied to local and regional earthquake recordings from the Marmara region in NW Turkey obtained by numerous permanent seismic stations from different local and regional networks. The substantially improved velocity model will allow for reliable absolute hypocenter determination which is of relevance especially in the light of the expected major (M7+) earthquake in the vicinity of the population center of Istanbul, where a combined surface and borehole-based seismometer network is to be installed in the frame of the ICDP-GONAF project. We expect to provide the first regional 3D-velocity model for this key-region.