Understanding Seismic Waves Generated by Train Traffic via Modeling: Implications for Seismic Imaging and Monitoring

Abstract

Trains are now recognized as powerful sources for seismic interferometry based on noise correlation, but the optimal use of these signals still requires a better understanding of their source mechanisms. Here, we present a simple approach for modeling train-generated signals inspired by early work in the engineering community, assuming that seismic waves are emitted by sleepers regularly spaced along the railway and excited by passing train wheels. Our modeling reproduces well seismological observations of tremor-like emergent signals and of their harmonic spectra. We illustrate how these spectra are modulated by wheel spacing, and how their high-frequency content is controlled by the distribution of axle loads over the rail, which mainly depends on ground stiffness beneath the railway. This is summarized as a simple rule of thumb that predicts the frequency bands in which most of train-radiated energy is expected, as a function of train speed and of axle distance within bogies. Furthermore, we identify two end-member mechanisms—single stationary source versus single moving load—that explain two types of documented observations, characterized by different spectral signatures related to train speed and either wagon length or sleeper spacing. In view of using train-generated signals for seismic applications, an important conclusion is that the frequency content of the signals is dominated by high-frequency harmonics and not by fundamental modes of vibrations. Consequently, most train traffic worldwide is expected to generate signals with a significant high-frequency content, in particular in the case of trains traveling at variable speeds that produce truly broadband signals. Proposing a framework for predicting train-generated seismic wavefields over meters to kilometers distance from railways, this work paves the way for high-resolution passive seismic imaging and monitoring at different scales with applications to near-surface surveys (aquifers, civil engineering), natural resources exploration, and natural hazard studies (landslides, earthquakes, and volcanoes).

Modeling P waves in seismic noise correlations: Advancing fault monitoring using train traffic sources

“…Solving equation ( 3) instead is costly, but might be feasible, since trains are constrained to specific locations in space. Setting up the power-spectral density distribution can then benefit from progress made in train traffic modeling (Lavoué et al 2020). Ayala-Garcia et al (2021) discuss the effects of correlated sources and present a new stacking strategy to mitigate them.…”

“…In previous experiments, promising observations were balanced by the difficulty of maintaining stable sources over the long-term that limits the capability of monitoring seismic velocities precisely and continuously over many years (Karageorgi et al 1992;Niu et al 2008;Tsuji et al 2018). Recent studies have shown that train traffic generates strong seismic radiation (Lavoué et al 2020). Brenguier et al (2019) and Pinzon-Rincon et al (2021) have used these train tremors to retrieve stable P waves using interferometry between arrays of sensors across the San Jacinto fault in California.…”

ModellingPwaves in seismic noise correlations: advancing fault monitoring using train traffic sources

“…( 3) instead is costly, but might be feasible, since trains are constrained to specific locations in space. Setting up the powerspectral density distribution can then benefit from progress made in train traffic modelling (Lavoué et al 2020). Ayala-Garcia et al (2021) discuss the effects of correlated sources and present a new stacking strategy to mitigate them.…”

“…In previous experiments, promising observations were balanced by the difficulty of maintaining stable sources over the long-term that limits the capability of monitoring seismic velocities precisely and continuously over many years (Karageorgi et al 1992;Niu et al 2008;Tsuji et al 2018). Recent studies have shown that train traffic generates strong seismic radiation (Lavoué et al 2020). Brenguier et al (2019) and Pinzon-Rincon (2021) have used these train tremors to retrieve stable P waves using interferometry between arrays of sensors across the San Jacinto fault in California.…”

Neutrons on Rails: Transregional Monitoring of Soil Moisture and Snow Water Equivalent

“…While railway infrastructure is already attracting some interest in the field of applied geophysics (Ižvolt et al, 2016;Lavoué et al, 2021), the present feasibility study specifically pushes the current limitation of mobile CRNS toward transregional monitoring. We will begin with theoretical considerations about the expected measurement uncertainty and spatial resolution, followed by a sensitivity study on the influence of vehicles and track beds using numerical simulations.…”