Modelling P waves in seismic noise correlations: advancing fault monitoring using train traffic sources

The theory of Green's function retrieval essentially requires homogeneously distributed noise sources. Even though these conditions are not fulfilled in nature, low-frequency (<1 Hz) surface waves generated by ocean-crust interactions have been used successfully to image the crust with unprecedented spatial resolution. In contrast to low-frequency surface waves, high-frequency (>1 Hz) body waves have a sharper, more localized sensitivity to velocity contrasts and temporal changes at depth. In general, their retrieval using seismic interferometry is challenging, and recent studies focus on powerful, localized noise sources. They have proven to be a promising alternative but break the assumptions of Green's function retrieval. In this study, we present an approach to model correlations between P waves for these scenarios and analyse their sensitivity to 3-D Earth structure. We perform a series of numerical experiments to advance our understanding of these signals and prepare for an application to fault monitoring. In the considered cases, the character of the signals strongly diverges from Green's function retrieval, and the sensitivity to structure has significant contributions in the source direction. An accurate description of the underlying physics allows us to reproduce observations made in the context of monitoring the San Jacinto Fault in California using train-generated seismic waves. This approach provides new perspectives for detecting and localizing temporal velocity changes previously unnoticed by commonly exploited surface-wave reconstructions.

Automated summary

The theory of Green's function retrieval requires homogeneously distributed noise sources, but low-frequency surface waves from ocean-crust interactions have been successfully used to image the crust with high spatial resolution. High-frequency body waves have sharper sensitivity to velocity contrasts and temporal changes at depth, with recent studies focusing on powerful, localized noise sources. Modeling correlations between P waves and analyzing their sensitivity to 3-D Earth structure is crucial for understanding and applying seismic interferometry in fault monitoring.