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Seismic velocities in rocks are highly sensitive to changes in permanent deformation and fluid content. The temporal variation of seismic velocity during the preparation phase of earthquakes has been well documented in laboratories but rarely observed in nature. It has been recently found that some anthropogenic, high‐frequency (>1 Hz) seismic sources are powerful enough to generate body waves that travel down to a few kilometers and can be used to monitor fault zones at seismogenic depth. Anthropogenic seismic sources typically have fixed spatial distribution and provide new perspectives for velocity monitoring. In this work, we propose a systematic workflow to seek such powerful seismic sources in a rapid and straightforward manner. We tackle the problem from a statistical point of view, considering that persistent, powerful seismic sources yield highly coherent correlation functions (CFs) between pairs of seismic sensors. The algorithm is tested in California and Japan. Multiple sites close to fault zones show high‐frequency CFs stable for an extended period of time. These findings have great potential for monitoring fault zones, including the San Jacinto Fault and the Ridgecrest area in Southern California, Napa in Northern California, and faults in central Japan. However, extra steps, such as beamforming or polarization analysis, are required to determine the dominant seismic sources and study the source characteristics, which are crucial to interpreting the velocity monitoring results. Train tremors identified by the present approach have been successfully used for seismic velocity monitoring of the San Jacinto Fault in previous studies. Plain Language Summary: Temporal variations of seismic velocities in the vicinity of fault zones are informative for understanding the earthquake preparation phase, but the lack of appropriate methodology and observations hinders actual applications. Human activities generate strong seismic energy that is suitable for monitoring velocity changes at depth. We design an algorithm to search for persistent anthropogenic seismic sources for fault‐zone velocity monitoring, and the workflow can be generalized to other applications. The feasibility of our algorithm is tested on three different data sets in California and Japan. We find stable sources close to several important fault zones that have hosted or have the potential to host large earthquakes. This study paves the way for future works related to fault‐zone velocity monitoring. Key Points: Repeating anthropogenic seismic sources are useful for seismic velocity monitoringWe use the stability of correlation functions over time as a proxy to search for persistent seismic sourcesCase studies in California and Japan demonstrate the potential for fault zone monitoring [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Laboratory experiments report that detectable seismic velocity changes should occur in the vicinity of fault zones prior to earthquakes. However, operating permanent active seismic sources to monitor natural faults at seismogenic depth is found to be nearly impossible to achieve. We show that seismic noise generated by vehicle traffic, and especially heavy freight trains, can be turned into a powerful repetitive seismic source to continuously probe the Earth's crust at a few kilometers depth. Results of an exploratory seismic experiment in Southern California demonstrate that correlations of train‐generated seismic signals allow daily reconstruction of direct P body waves probing the San Jacinto Fault down to 4‐km depth. This new approach may facilitate monitoring most of the San Andreas Fault system using the railway and highway network of California. Plain Language Summary: Even though laboratory experiments report that they should be preceded by detectable precursors, earthquakes remain unpredictable. Indeed, contrary to the lab, scanning natural faults at a few kilometers depth where earthquakes initiate requires operating high‐energy seismic sources continuously in time, which is found to be nearly impossible. In this study, we show that large freight trains generate sufficient seismic energy to travel down to a few kilometers depth and be detected at tens of kilometers from railways. We demonstrate that we can turn this apparently random source of seismic signal into an impulsive virtual seismic source to monitor active faults. We finally estimate that this new approach can be used for monitoring most of the San Andreas Fault system using the railway and highway network of California. Key Points: Freight trains in Southern California are locally equivalent to a magnitude 2.2 earthquake every dayWe use train noise to reconstruct repetitive virtual sources of P waves crossing the San Jacinto Fault at 4‐km depthPredictions of train noise across California show potential for passive monitoring of most of the San Andreas Fault system [ABSTRACT FROM AUTHOR]