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Cross-correlation imaging of ambient noise sources

AuthorsErmert, L.; Villaseñor, Antonio ; Fichtner, Andreas
Inverse theory
Surface waves and free oscillations
Wave propagation
Issue Date2016
PublisherOxford University Press
CitationGeophysical Journal International, 204(1): 347-364 (2016)
AbstractWe develop and apply a novel technique to image ambient seismic noise sources. It is based on measurements of cross-correlation asymmetry defined as the logarithmic energy ratio of the causal and anticausal branches of the cross-correlation function. A possible application of this technique is to account for the distribution of noise sources, a problem which currently poses obstacles to noise-based surface wave dispersion analysis and waveform inversion. The particular asymmetry measurement used is independent of absolute noise correlation amplitudes. It is shown how it can be forward-modelled and related to the noise source power-spectral density using adjoint methods. Simplified sensitivity kernels allow us to rapidly image variations in the power-spectral density of noise sources. This imaging method correctly accounts for viscoelastic attenuation and is to first order insensitive to unmodelled Earth structure. Furthermore, it operates directly on noise correlation data sets. No additional processing is required, which makes the method fast and computationally inexpensive.We apply the method to three vertical-component cross-correlation data sets of different spatial and temporal scales. Processing is deliberately minimal so as to keep observations consistent with the imaging concept. In accord with previous studies, we image seasonally changing sources of the Earth's hum in the Atlantic, Pacific and the Southern Ocean. The sources of noise in the microseismic band recorded at stations in Switzerland are predominantly located in the Atlantic and show a clear dependence on both season and frequency. Our developments are intended as a step towards full 3-D inversions for the sources of ambient noise in various frequency bands, which may ultimately lead to improvements of noise-based structural imaging.
Publisher version (URL)http://dx.doi.org/10.1093/gji/ggv460
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