A fundamental problem associated with event identification lies in deriving corrections that remove source and path effects on regional phase amplitudes used to construct discriminants. Our goal is to derive a set of physically based corrections that are independent of magnitude and distance, and amenable to multivariate discrimination by extending the technique described in Taylor and Hartse (1998).
For a given station and source region, a number of well-recorded earthquakes are used to estimate source and path corrections. The source model assumes a simple Brune (1970) earthquake-source that has been extended to handle non-constant stress drop.
The propagation model consists of a frequency-independent geometrical spreading and frequency-dependent power-law Q. A large-scale search is performed simultaneously at each station for all recorded regional phases over stress-drop, geometrical spreading, and frequency-dependent Q to find a suite of good-fitting models that remove the dependence on mb and distance.
Seismic moments can either be inverted for or fixed and are tied to mb through two additional coefficients. We also solve for frequency-dependent site/phase excitation terms.
Once a set of corrections is derived, effects of source scaling and distance as a function of frequency are applied to amplitudes from new events prior to forming discrimination ratios. Thus, all the corrections are tied to just mb and distance and can be applied very rapidly in an operational setting. Moreover, phase amplitude residuals as a function of frequency can be spatially interpolated (e.g. using Kriging) and used to construct a correction surface for each phase and frequency. The spatial corrections from the correction surfaces can then be applied to the corrected amplitudes based only on the event location. The correction parameters and correction surfaces can be developed offline and entered into an online database for pipeline processing providing multivariate-normal corrected amplitudes for event identification.
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