Robust seismic velocity change estimation using ambient noise recordings

TL;DR

This paper investigates how seasonal fluctuations in ambient noise sources affect seismic velocity change estimation and proposes a normalization method to improve accuracy, validated through simulations and real data.

Contribution

It introduces a normalization technique to mitigate seasonal noise effects in seismic velocity change estimation, enhancing reliability of ambient noise methods.

Findings

Normalization reduces misleading velocity variations caused by seasonal fluctuations.

The method improves the signal-to-noise ratio in velocity change estimates.

Numerical and real data confirm the effectiveness of the proposed approach.

Abstract

We consider the problem of seismic velocity change estimation using ambient noise recordings. Motivated by [23] we study how the velocity change estimation is affected by seasonal fluctuations in the noise sources. More precisely, we consider a numerical model and introduce spatio-temporal seasonal fluctuations in the noise sources. We show that indeed, as pointed out in [23], the stretching method is affected by these fluctuations and produces misleading apparent velocity variations which reduce dramatically the signal to noise ratio of the method. We also show that these apparent velocity variations can be eliminated by an adequate normalization of the cross-correlation functions. Theoretically we expect our approach to work as long as the seasonal fluctuations in the noise sources are uniform, an assumption which holds for closely located seismic stations. We illustrate with numerical simulations and real measurements that the proposed normalization significantly improves the accuracy of the velocity change estimation.