Global‐Scale Full‐Waveform Ambient Noise Inversion

Abstract

We present the first application of full-waveform ambient noise inversion to observed correlation functions that jointly constrains 3-D Earth structure and heterogeneous noise sources. For this, we model and interpret ambient noise correlations as recordings of correlation wavefields, which completely eliminates the limiting assumptions of Green's function retrieval, such as equipartitioning and homogeneous random noise sources. Our method accounts for seismic wave propagation physics in 3-D heterogeneous and attenuating media and also for the heterogeneous and nonstationary nature of the ambient noise field. Designed as a proof of concept, the study considers long periods from 100 to 300 s, thus focusing on the Earth's hum. Treating correlations as self-consistent observables allows us to make separate measurements on the causal and acausal branches of correlation functions, without any need to choose one of them or form the average. We validate our approach by assessing the quality of the obtained models and by comparing them to previous studies. This work is a step toward the establishment of full-waveform ambient noise inversion as a tomographic technique with the goal to go beyond ambient noise tomography based on Green's function retrieval.

Introducing noisi: a Python tool for ambient noise cross-correlation modeling and noise source inversion

“…Cross-correlations of ambient seismic noise form the basis of many applications in seismology from site effects studies (e.g., Aki, 1957;Roten et al, 2006;Bard et al, 2010;Denolle et al, 2013;Bowden et al, 2015) to ambient noise tomography (e.g., Shapiro et al, 2005;Yang et al, 2007;Nishida et al, 2009;Haned et al, 2016;de Ridder et al, 2014;Fang et al, 2015;Singer et al, 2017) and coda wave interferometry (e.g., Sens-Schönfelder and Wegler, 2006;Brenguier et al, 2008;Obermann et al, 2013;Sánchez-Pastor et al, 2019). Auto-correlations of the ambient noise are also increasingly used to study seismic interfaces as suggested by Claerbout (1968) (e.g., Taylor et al, 2016;Saygin et al, 2017;Romero and Schimmel, 2018) and to monitor subsurface properties (Viens et al, 2018;Clements and Denolle, 2018).…”

Rapid finite-frequency microseismic noise source inversion at regional to global scales

“…An alternative to the direct discretisation of Eq. (6) combined with a Green's function database is on-the-fly computation of the correlation wavefield source G jm (x 2 , ξ)S nm (ξ) on the grid of a numerical wave propagation solver, and its use in a subsequent forward simulation (Tromp et al 2010;Fichtner 2014;Sager et al 2020). This approach trades the larger storage requirements of the Green's function database for larger computational requirements in an iterative inversion, where correlations must be computed for a sequence of noise source updates.…”

“…Even though it has been shown that the measurement is quite robust to unknown 3-D Earth structures (Sager et al 2018a), this could still lead to artifacts in the inversion. Sager et al (2020) invert for both, the structure and noise distribution simultaneously. This does, however, greatly increase the computational resources necessary to perform an inversion; particularly when considering high-frequency noise like the secondary microseisms.…”

“…Tromp et al 2010;Hanasoge 2013b;Fichtner et al 2017;Ermert et al 2017;Sager et al 2018b;Datta et al 2019;Xu et al 2019) and are reaching the level of being applicable to data (e.g. Sager et al 2020;Xu et al 2020). However, these methods require knowledge of the noise source distribution.…”

Ambient Noise Seismic Interferometry Through Surface Seismic Data Acquisition vs Zero-Offset Vertical Seismic Profiling (Vsp)

“…Recently, Sager et al (2018) investigated the full waveform ambient noise inversion that aims to extract the Green's function. Sager et al (2020) presented the first application about full-waveform ambient noise inversion to image subsurface. Tkalčić et al (2020) utilizes coda wavefield to investigate the earth's deep structure in earthquake seismology.…”