4.6 Article

Interpreting cross-correlations of one-bit filtered seismic noise

Journal

GEOPHYSICAL JOURNAL INTERNATIONAL
Volume 195, Issue 3, Pages 1811-1830

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/gji/ggt337

Keywords

Theoretical seismology; Wave scattering and diffraction; Wave propagation

Funding

  1. NASA [NNX11AB63G]
  2. NASA [NNX11AB63G, 149745] Funding Source: Federal RePORTER

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Seismic noise, generated by oceanic microseisms and other sources, illuminates the crust in a manner different from tectonic sources, and therefore provides independent information. The primary measurable is the two-point cross-correlation, evaluated using traces recorded at a pair of seismometers over a finite-time interval. However, raw seismic traces contain intermittent large-amplitude perturbations arising from tectonic activity and instrumental errors, which may corrupt the estimated cross-correlations of microseismic fluctuations. To diminish the impact of these perturbations, the recorded traces are filtered using the non-linear one-bit digitizer, which replaces the measurement by its sign. Previous theory shows that for stationary Gaussian-distributed seismic noise fluctuations one-bit and raw correlation functions are related by a simple invertible transformation. Here we extend this to show that the simple correspondence between these two correlation techniques remains valid for non-stationary Gaussian and a very broad range of non-Gaussian processes as well. For a limited range of stationary and non-stationary Gaussian fluctuations, we find that one-bit filtering performs at least as well as spectral whitening. We therefore recommend using one-bit filtering when processing terrestrial seismic noise, with the substantial benefit that the measurements are fully compatible with current theoretical interpretation (e.g. adjoint theory). Given that seismic records are non-stationary and comprise small-amplitude fluctuations and intermittent, large-amplitude tectonic/other perturbations, we outline an algorithm to accurately retrieve the correlation function of the small-amplitude signals.

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