Seismic interferometry from correlated noise sources

TL;DR

This paper investigates the impact of correlated noise sources on seismic interferometry, revealing significant errors and proposing a new workflow to mitigate these effects, thereby enhancing subsurface imaging accuracy.

Contribution

It introduces a novel analytical approach and workflow to reduce errors caused by correlated noise sources in seismic interferometry, improving the reliability of Green's function estimates.

Findings

Correlated noise sources significantly perturb Green's function estimates.

Stacking reduces phase errors but does not fully eliminate issues caused by correlation.

The proposed workflow effectively mitigates errors from correlated ambient noise.

Abstract

It is a well-established principle that cross-correlating seismic observations at different receiver locations can yield estimates of band-limited inter-receiver Green's functions. This principle, known as seismic interferometry, is a powerful technique that can transform noise into signals which allow us to remotely image and interrogate subsurface Earth structures. In practice it is often necessary and even desirable to rely on noise already present in the environment. Theory that underpins many applications of ambient noise interferometry makes an assumption that the noise sources are uncorrelated in space and time. However, many real-world noise sources such as trains, highway traffic and ocean waves are inherently correlated both in space and time, in direct contradiction to the current theoretical foundations. Applying standard interferometric techniques to recordings from correlated energy sources makes the Green's function liable to estimation errors that so far have not been fully accounted for theoretically nor in practice. We show that these errors are significant for common noise sources, always perturbing and sometimes obscuring the phase one wishes to retrieve. Our analysis explains why stacking may reduce the phase errors, but also shows that in commonly-encountered circumstances stacking will not remediate the problem. This analytical insight allowed us to develop a novel workflow that significantly mitigates effects arising from the use of correlated noise sources. Our methodology can be used in conjunction with already existing approaches, and improves results from both correlated and uncorrelated ambient noise. Hence, we expect it to be widely applicable in real life ambient noise studies.