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Seismo Lab Brown Bag Series

Tuesday, July 2, 2024
12:00pm to 1:00pm
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South Mudd 256 (Benioff Room)
Correlation methods of earthquake coda in seismic body wave studies of the Earth's interiors
Thanh-Son Pham, Postdoctoral Fellow, Australian National University,

The discovery of long-range spatial correlation in earthquake coda and ambient noise records has had far-reaching impacts on modern seismology. This approach provides a conceptual framework to extract information about the structure of the Earth from stacked cross-correlations as a function of inter-receiver distance (i.e., correlograms) using noisy seismic records. Early work concentrated on retrieving surface waves traveling between receiver pairs from ambient noise and used measurements of their dispersion in surface wave tomography applications. Later, it was found that body-wave-like signals also emerge in correlograms. Intriguingly, many feeble signals sensitive to deep Earth structures can also be 'extracted' efficiently from the late coda of large earthquakes. Yet, the nature of correlation features in coda correlograms has remained a puzzle. Disentangling that puzzle is a key to opening new avenues for deep Earth studies.

This talk will revisit recent theoretical and observational advancements in correlation methods using (i) wave trains immediately following primary teleseismic arrivals or (ii) extended coda after large earthquakes. The former instance is relevant to a local scale technique, the teleseismic P-wave coda autocorrelation, which has proved efficient in imaging shallow stratified layers. The latter gives rise to an emerging concept of a global correlation wavefield. All features in the correlation wavefield result from the similarity of the waveforms of two regular seismic phases sharing a subset of propagation legs. The new concepts have provided novel insights into the Earth and planetary deep interiors, which I will introduce briefly.

For more information, please contact Donna Mireles by phone at 626-395-6952 or by email at dmireles@caltech.edu.