Abstract
The precise estimation of associated parameters for microseismic and earthquake signals is a challenging task due to the presence of background noise. Important parameters to analyze earthquake signals such as peak ground acceleration, velocity, displacement, and P, S-wave arrival time are affected by noise. In this study, we propose a seismic data denoising algorithm by combining variational mode decomposition (VMD) and Savitzky-Golay (SG) filter. The method first employs a VMD technique that disintegrates the original signal into band-limited intrinsic mode functions. The modes that are contaminated with high-frequency noise are selected and smoothed by the SG filter. An important advantage of SG filters is their ability to retain the shape of data with high frequency. To observe the effect of noise, PPHASEPICKER is applied to the signal provided by the proposed denoising method. As the fundamental constituent of the earthquake accelerogram is displacement, we performed an experiment to expose the effect of noise and different denoising techniques on the displacement component. The results of synthetic data and real data from the Nepal 2015 earthquake show the enhancement of signal-to-noise ratio while preserving the significant features of the displacement component and onset time arrival accuracy, in comparison with some existing techniques.
Published Version
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