Constraining on the Stationarity of Signal with Time-Frequency Surrogates to Enhance the Reliability of Singularity Spectrum Attributes of Random Seismic Noise Wavefield

Abstract. Existence of a self-affine long range persistence in the seismic noise time series evidences that the current state of system is not in the pure diffused regime and transition from coherent to incoherent motion is still on progress. Rate of this evolving transition can be indirectly linked to the degree of heterogeneity of medium, thus in this paper we tried to gain an insight into the heterogeneity of the medium by analyzing the width, extreme and asymmetrical trend of multifractal spectrum of seismic records. Nonetheless, toward high frequency ranges a seismic signal itself loses its stationarity short while after its recording onset time. Experimentally, the long-range correlation of a stationary time series (with 0 < h(2) < 1) can be discerned from a non-stationary process (with h(2) > 1) by examining the values of scaling exponent h(2), however, changing in the fractal properties in the crossover time scales in time series don’t permit us to ascribe a single amount for h(2) and without executing additional analysis on the stationarity length of signals, direct calculation of such long range correlation and fractal dimensions might be biased. Hence, in this paper we examined the inherent stationarity of a signal relative to the different observation scales in the stochastic contexts before feeding the signal into the cycle of DFA. This method is based on the comparison between global and local features of the original signal and its synthesized time-frequency surrogates; therefor it can effectively improve the accuracy of results. Our approach proves the existence of a high-velocity anomalous feature in the right flank of Sahand inactive volcano where it is surrounded by heterogeneous low-velocity structures and extended to the shallower than ~ 3 km depth beneath this region at the northwestern of Iran.