Wavelet-based Semblance Filtering of Geophysical Data and Its Application

Wavelet transform has been widely used in terms that it may overcome the shortcoming of conventional Fourier transform. Fourier transform has its difficulty to explain how the transformed domain, frequency, is related with time. Traditional semblance technique in Fourier transform was devised to compare two time series on the basis of their phase as a function of frequency. But this method is known not to work well for the non-stationary signal. In this study, we present two applications of the wavelet-based semblance method to geophysical data. Firstly, we show filtered geomagnetic signal remained with components of high correlation to each observatory. Secondly, highly correlated residual signal of gravity and magnetic survey data, which are also filtered by this semblance method, is present.