Using a fractal analysis and polarization method for phase identification in three-component seismograms

Abstract

This study presents the automatic P-wave and S-wave arrivals picking algorithm which is essentially based on the fractal dimension and polarized method. With an estimate of the spectral exponent γ in a 1/f process, an interval that indicates the preferred intersection containing both noise and the P-wave is well-detected by corresponding to the minimum absolute spectral exponent γvalue along the trace. Based on the different properties of background noise and deterministic signal, the fractal dimension technique can detect the position of the P-wave. The place where the fractal dimension value changes suddenly within the intersection interval indicates the location of arrival of the P-wave. Testing that adds various levels of noise to the seismic signal shows the method can prove able to tolerate noise to a signal-to-noise (S/N) ratio 1.5. Based on the P-wave arrival, the polarized P-wave could be detected by a genetic algorithm (GA) with the strength of polarization and phase difference between the vertical and horizontal components as constraints. Using the first arrival phase as the basis phase, this study combines a polarization filter including rectilinearity functions, linear polarization, phase difference and directionality with GA to detect polarized S-wave of seismograms. Finally, the technique was applied to teleseismic data and near-field motion to verify the accuracy and wide applicability of this method. To conclude, this proposed method, an efficient and brand-new method of associating signal processing technique with physical wave motion properties, may be of importance in finding P-wave and S-wave phase arrivals accurately using three-component seismograms.