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Abstract
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The picking of the seismic phase arrival can be defined as the detection of the instant of time when the first energy of the phase (the longitudinal P-phase) arrives at a seismometer. Such arrivals are often identified by a change from the background noise, in energy, amplitude, frequency contents or wave polarization. Seismic phase arrival time identification enables scientists to derive important geophysical and seismological information, such as the structure of the earth’s interior, geotectonic settings, seismicity of an area and seismic hazard assessment. Also the automatic seismic phases picking are of great importance in seismic data processing, especially in location and tomography that can be regarded as tow bold examples. A seismic network or even a single station operating continuously at high sampling frequency produces an enormous amount of data, processing of such a volume of waveforms manually is very time-consuming and require considerable manpower. In addition, due to human error, incorrect detection of the phase can affect future studies. Therefore, it is needed to an alternative more efficient, faster, and accurate method that reduce the human, financial and time costs and also decrease the probability of errors. Hence, in recent decades, significant efforts have been made to develop automatic phase picking methods. In this study, the version of the Undecimated Wavelet Transform (UWT) or the Maximum Overlap Discrete Wavelet Transform (MODWT) is used to determine and picking the arrival time the P and S phases. The methodology of this study is divided into two parts: the first part is about the determination of the P arrival time obtained by processing the stacked envelop of the wavelet transform coefficients. The second part is determining the S arrival time, which is done using wavelet transform (WT) and AR model. the estimation of arrival time of the S wave is done in two steps. At first, an initial estimation of arrival time is calculated using
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