HR: 1340h
AN: S33A-1079    [Abstracts]
TI: Delay Times From Clustered Multi-Channel Cross Correlation and Simulated Annealing
AU: * Creager, K C
EM: creager@ess.washington.edu
AF: University of Washington, Dept. Earth and Space Sciences, Seattle, WA 98195-1310 United States
AU: Sambridge, M S
EM: malcolm.sambridge@anu.edu.au
AF: Australian National University, Research School of Earth Sciences, Canberra, ACT 0200 Australia
AB: Several techniques exist to estimate relative delay times of seismic phases based on the assumption that the waveforms observed at several stations can be expressed as a common waveform that has been time shifted and distorted by random uncorrelated noise. We explore the more general problem of estimating the relative delay times for regional or even global distributions of seismometers in cases where waveforms vary systematically across the array. The estimation of relative delay times is formulated as a global optimization of the weighted sum of squares of cross correlations of each seismogram pair evaluated at the corresponding difference in their relative delay times. As there are many local minima in this penalty function, a simulated annealing algorithm is used to obtain a solution. The weights depend strongly on the separation distance among seismogram pairs as well as a measure of the similarity of waveforms. Thus, seismograph pairs that are physically close to each other and have similar waveforms are expected to be well aligned while those with dissimilar waveforms or large separation distances are severely down-weighted and thus need not be well aligned. As a result noisy seismograms, which are not similar to other seismograms, are down-weighted so they do not adversely effect the relative delay times of other seismograms. Finally, natural clusters of seismograms are determined from the weight matrix. Examples of aligning a few hundred P and PKP waveforms from a broadband global array and from a mixed broadband and short-period continental-scale array will be shown. While this method has applications in many situations, it may be especially useful for arrays such as the EarthScope Bigfoot Array.
DE: 7294 Instruments and techniques
DE: 7203 Body wave propagation
DE: 3260 Inverse theory
DE: 0910 Data processing
SC: Seismology [S]
MN: 2004 AGU Fall Meeting