Seismic signal detection by fractal dimension analysis

Abstract

We introduce a new detection algorithm with improved local and regional seismic signal recognition. The method is based on the difference between seismic signals and background random noise in terms of fractal dimension D. We compare the new method extensively with standard methods currently in use at the Seismic Network of the lstituto Nazionale di Geofisica. Results from the comparisons show that the new method recognizes seismic phases detected by existing procedures, and in addition, it features a greater sensitivity to smaller signals, without an increase in the number of false alarms. The new method was tested on real continuous data and artificially simulated high-noise conditions and demonstrated a capability to recognize seismic signals in the presence of high noise. The efficiency of the method is due to a radically different approach to the topic, in that the assertion that a signal is fractal implies a relationship between the spectral amplitude of different frequencies. This relationship allows, for the fractal detector, a complete analysis of the entire frequency range under consideration.