Determination of Near-Station Crustal Structure and the Regional Seismic Event Location Problem,
Abstract
Since crustal structure strongly influences the character of regional seismic waveforms, a knowledge of near-station crustal structure is necessary for obtaining single-station event locations of small (M-3) seismic events. In this study we demonstrate that it is practical to use a receiver-function method for determining near-station crustal structure; then, we then use this structure as a basis for constructing synthetic waveforms, and determine single-station regional event locations by comparing the synthetic and observed waveforms. Our receiver-function approach for determining crustal structure utilizes vertical-component P-group waveforms from teleseismic events as input for synthesizing a radial-component waveform for a trial, layered, near-station crustal model. Then, we compare the synthetic and observed radial-component waveforms, and change the crustal model until they are sufficiently similar. To improve efficiency we have implemented several features in our software: For synthesizing radial-component waveforms from vertical-component data we employ a theoretical approximation which is exact to second order in the reflection and transmission coefficients; thus, we call this second-order, radial-vertical comparison the SORVEC method; For synthesizing reverberation waveforms for a n-layer-over-a-halfspace crustal model we show it is generally sufficient to calculate amplitudes for only (6n+l) carefully selected rays; To determine crustal structure we have developed an inversion scheme which utilizes a very fast simulated annealing (VFSA) algorithm which is much faster than grid-search methods, Monte-Carlo methods, or ordinary simulated annealing methods. Using the SORVEC-VFSA algorithm we have determined flat-layered crustal models beneath 12 seismic stations, one (PAS) in California and 11 in Tibet.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 14, 1995
- Accession Number
- ADP204514
Entities
People
- Cliff Frohlich
- Lian-she Zhao
Organizations
- University of Texas at Austin