Denoising Surface Waves Extracted From Ambient Noise Recorded by 1‐D Linear Array Using Three‐Station Interferometry of Direct Waves. Issue 8 (2nd August 2021) - Qiu, Hongrui; Niu, Fenglin; Qin, Lei
Abstract: We develop an automatic workflow for enhancing surface wave signals in ambient noise cross correlations (ANCs) calculated for a one‐dimensional (1‐D) linear array. 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. Fundamental and higher modes of surface waves are observed in ANCs of the nodal array. After attenuating the surface wave overtones by applying a frequency‐dependent tapering window to the ANCs, signals dominated by the fundamental mode surface wave are then enhanced through a denoising process based on three‐station interferometry of direct waves. The signal‐to‐noise ratio is significantly increased at high frequencies (>2 Hz) after denoising. Phase travel times are extracted reliably in the frequency domain for the period ranges of 0.3–1.2 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 (500–1, 000 m) low‐velocity zone that narrows with increasing period is observed, illuminating a flower‐shaped structure of the San Jacinto fault damage zone. Plain Language Summary: Properties of fault damage zone (width of 100–1, 000 m), such as its geometry and velocity reduction compared to the surrounding host rock, can have a profound impact on our understandings of earthquake ruptures and the long‐term behavior of the fault. Several dense nodal arrays with 10–100 m spacing and aperture of a few kilometers were deployed crossing surface traces of major faults, to provide high‐resolution images of the fault zone internal structures. Surface waves travel at frequency‐dependent speeds between every two sensors are observed in ambient noise cross correlations. We can infer structures at different depth using surface wave, as the velocity at higher frequency is more sensitive to shallower structures. However, surface waves extracted from ambient noise at high frequencies (>1 Hz), that are essential to image fault zone in the top hundreds of meters, are often very noisy. Here, we develop a denoising method that utilizes three‐station interferometry to effectively suppress non‐surface wave signals in a linear 1‐D array. The quality of surface waves is significantly improved after the denoising, especially at high frequencies (>2 Hz). Reliable measurements at high frequencies provide better constraints on fault zone internal structures at shallow depth. Key Points: Surface waves from ambient noise cross correlations are significantly enhanced at high frequencies using three‐station interferometry Phase travel times are extracted reliably between 0.3 and 1.6 s for a 1.6 km‐long linear array and are used to perform surface wave tomography Phase velocity models of Rayleigh and Love waves derived via eikonal tomography reveal high‐resolution fault zone images