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

在利用高精度地震震源位置确定目标区域的构造特征时，对三维速度结构的精确了解是一个重要的先决条件。在这方面，从大量的波形数据档案中选择准确的相位到达时间是最重要的输入参数。该项目的目的是开发自动识别和准确计时地壳相及其反演的算法，以得出土耳其西北部更广泛的马尔马拉地区的三维速度模型。基于P相和S相自动拾取算法的最新进展，计划将这些算法扩展和应用于额外的地壳和上地幔相，如PG、Pn、PMP和S波垂。根据最近的结果，我们将使用统计建模、多变量时间序列分析和启发式方法。新的方法还应该提供可靠的、非离散的和非对称的导出相移时间的误差估计。识别出的不同相位起始点的到达时间将作为非线性定位方法的输入，以建立最小一维速度模型，然后该模型将作为使用SIMULPS14进行三维反演的起始模型。新开发的算法将应用于土耳其西北部马尔马拉地区的地方和区域地震记录，这些记录是由来自不同地方和区域网络的许多永久地震台获得的。大大改进的速度模型将能够可靠地确定绝对震源，特别是考虑到伊斯坦布尔人口中心附近预计将发生大地震(M7+)，将在ICDP-GONAF项目框架内安装地面和井下组合的地震仪网络。我们希望为这一关键区域提供第一个区域三维速度模型。

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.