Denoising surface waves extracted from ambient noise using three-station
interferometry: Methodology and application to 1-D linear array
Abstract
We develop an automatic workflow for denoising the fundamental mode
surface wave from ambient noise cross correlations (ANCs) calculated for
a dense linear array. The surface wave signal traveling between each
station pair is first enhanced through three-station interferometry.
Then, phase travel times at different periods are determined in the
frequency domain. The proposed array-based method is applied to a
1.6-km-long dense linear nodal array crossing surface traces of the San
Jacinto fault near Anza, California. Surface wave signals in ANCs of the
nodal array are significantly enhanced after denoising, particularly at
high frequencies (> 2 Hz). Phase travel times are extracted
reliably in the period ranges of 0.3-1.3 s and 0.3-1.6 s for Rayleigh
and Love waves, respectively. The corresponding period-dependent phase
velocity profiles derived from the eikonal equation reveal
high-resolution details of fault zone internal structures beneath the
array. A broad (500-1000 m) low-velocity zone that narrows with
increasing period is observed, illuminating a flower-shaped structure of
the San Jacinto fault damage zone.