1887

Abstract

Summary

Due to climate imbalance, events such as landslides and sinkholes are expected to increasingly threaten aging railway networks, leading to serious safety concerns, material damage, and higher maintenance costs. To mitigate the risk of infrastructure failure, a predictive maintenance strategy based on geotechnical information is essential. However, acquiring direct geotechnical measurements through boreholes with adequate spatial and temporal resolution is both challenging and expensive. Geophysical methods can provide physical parameters that can be translated into key geotechnical indicators, such as earthwork stiffness or critical velocity. The main challenge lies in capturing this information over time. While snapshot imaging is feasible, continuous monitoring to track temporal changes remains complex and demanding.

This case study illustrates a four-year passive seismic monitoring campaign conducted in eastern France, along a railway segment prone to sinkhole formation. The rail segment was instrumented with a wired accelerometer network and continuously monitored, with trains acting as natural seismic sources. The approach demonstrates the reliability of seismic interferometry, using surface waves generated by passing trains to enable imaging of the near-surface structure.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202520141
2025-09-07
2026-02-11
Loading full text...

Full text loading...

References

  1. Bardainne, T., Cai, C., Rebert, T., TarnusR., Allemand, T., [2023a]. Passive seismic monitoring using trains as sources to characterize near-surface and prevent sinkholes. 84th EAGE Annual Conference, Volume 2023, p.1 – 5.
    [Google Scholar]
  2. Bardainne, T., Vivin, L., Tarnus, R., [2023b]. Railway near-surface passive seismic using trains as sources and fiber optic monitoring. NSG2023 3rd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM.
    [Google Scholar]
  3. Campillo, M. & Paul, A., [2003]. Long-range correlations in the diffuse seismic coda, In Science, 299(5606), 547. 18, 87.
    [Google Scholar]
  4. ChangJ. P., de RidderS.A. and BiondiB. L., [2016]. High-frequency Rayleigh-wave tomography using traffic noise from Long Beach, California, In Geophysics, 81: B43–B53.
    [Google Scholar]
  5. CunhaTexeira, J., Bodet, L., RivièreA., Hallier, A., GesretA., DangeardM., DhemaiedA. and Boisson GaboriauJ., [2025]. Physics-guided deep learning model for daily groundwater table maps estimation using passive surface-wave dispersion. In Water Resources Research.
    [Google Scholar]
  6. Quiros, D. A., Brown, L. D., and Kim, D., [2016]. Seismic interferometry of railroad induced ground motions: body and surface wave imaging. Geophysical Journal International, Volume 205, Issue 1, Pages 301–313.
    [Google Scholar]
  7. ThevenetE., Toubiana, H., Trafford, A., Donohue, S., Harms, J., Bardainne, T., [2024]. Assessing 3D slope condition with fibre optic seismic using trains as sources. NSG 2024 30th European Meeting of Environmental and Engineering Geophysics, Sep 2024, Volume 2024, p.1 – 5.
    [Google Scholar]
/content/papers/10.3997/2214-4609.202520141
Loading
/content/papers/10.3997/2214-4609.202520141
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error