Depth-phase identification by prediction-error filtering. I. Analysis of synthetic explosion signals

Details Depth-phase identification by prediction-error filtering. I. Analysis of synthetic explosion signals Depth-phase identification by prediction-error filtering. I. Analysis of synthetic explosion signals

Apr 1989

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1989pepi...54..210r&link_type=abstract

Physics of the Earth and Planetary Interiors, Volume 54, Issue 3-4, p. 210-230.

Physics

1

Scientific paper

For detecting depth phases from synthetic explosion seismograms, a parametric model for the P signal has been adopted. In other words, the primary P phase is characterized by numerical values of a few parameters. As the surface-reflected P phase will be almost identical with the P phase, the same model will also be valid for these phases. For seismic signals, a special type of parametric model, called an autoregressive (AR) model, is found useful. It is shown that the prediction-error filter (PEF) for a given order, as computed by AR modelling, is almost the same for the primary P phase as for the composite wave comprising the primary P phase and several reflected and refracted phases. Consequently, as the composite wave is convolved with its PEF, there will be large `local' errors around the `instants' when the reflected or refracted phases start entering the seismogram, thereby facilitating the identification of such phases. It is shown that using any order of the PEF, not necessarily the optimum, the depth phases can be extracted from the seismograms. However, in order to detect the depth phases unambiguously, the delay time of the depth phases with respect to the P phase should be > 0.3 s. For weak signals (e.g. signal-to-noise ratio, SNR ~2), synthesized array beams were successfully used to extract the depth phases. It is also demonstrated that lower T* (travel time/quality factor ratio) values, say 0.6 s, tend to give better results than T* = 1.0 s.

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