F. Lavoué, O. Coutant, P. Boué, L. Pinzon‐Rincon, F.Brenguier, R. Brossier, P. Dales, M. Rezaeifar, C. J. Bean; Understanding Seismic Waves Generated by Train Traffic via Modeling: Implications for Seismic Imaging and Monitoring. Seismological Research Letters (2020)
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).
P. Dales, L. Pinzon-Ricon, F. Brenguier, et al. . Virtual Sources of Body Waves from Noise Correlations in a Mineral Exploration Context. Seismological Research Letters. Seismological Research Letters (2020) 91 (4): 2278–2286.
The extraction of body waves from passive seismic recordings has great potential for monitoring and imaging applications. The low environmental impact, low cost, and high accessibility of passive techniques makes them especially attractive as replacement or complementary techniques to active‐source exploration. There still, however, remain many challenges with body‐wave extraction, mainly the strong dependence on local seismic sources necessary to create high‐frequency body‐wave energy. Here, we present the Marathon dataset collected in September 2018, which consists of 30 days of continuous recordings from a dense surface array of 1020 single vertical‐component geophones deployed over a mineral exploration block. First, we use a cross‐correlation beamforming technique to evaluate the wavefield each minute and discover that the local highway and railroad traffic are the primary sources of high‐frequency body‐wave energy. Next, we demonstrate how selective stacking of cross‐correlation functions during periods where vehicles and trains are passing near the array reveals strong body‐wave arrivals. Based on source station geometry and the estimated geologic structure, we interpret these arrivals as virtual refractions due to their high velocity and linear moveout. Finally, we demonstrate how the apparent velocity of these arrivals along the array contains information about the local geologic structure, mainly the major dipping layer. Although vehicle sources illuminating array in a narrow azimuth may not seem ideal for passive reflection imaging, we expect this case will be commonly encountered and should serve as a good dataset for the development of new techniques in this domain.
Brenguier, F., Boué, P., Ben‐Zion, Y., Vernon, F., Johnson, C. W., Mordret, A., et al. ( 2019). Train traffic as a powerful noise source for monitoring active faults with seismic interferometry. Geophysical Research Letters, 46.
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.
Chmiel, M., Mordret, A. , Boué, P., Brenguier, F., Lecocq, T., Courbis, R., Hollis, D, Campman, X., Romijn, R. and Van der Veen, W. (2019). Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field, Geophys. J. Int.
Hollis D., McBride J., Good D., Arndt N., Brenguier F., and Olivier G., 2018. Use of Ambient Noise Surface Wave Tomography in Mineral Resource Exploration and Evaluation, SEG Annual Meeting 2018, Anaheim, California.
Abstract: Passive seismic imaging is a low-impact, low-cost technique that can be used to explore for and evaluate mineral deposits. […]
The technique uses ambient seismic noise from natural and anthropogenic sources for subsurface imagining and monitoring. Cross-correlation between receiver pairs is used to extract the Green function and analysis of dispersion of surface wave from the cross-correlated data generates a near-surface velocity model. This model is then used to establish the structure, lithology, and physical characteristics of materials in the subsurface. The results can be used alone or jointly with other geophysical or geological data or employed to improve imagining of active source data.
The scales of passive seismic imaging range from the entire crust and upper mantle to near-surface geotechnical or civil engineering surveys, spanning depths from 100s of kilometers to few meters. Most current applications are in the petroleum, geothermal, groundwater and geo-engineering sectors but the technique is finding increasing employment in mine security and mineral exploration.
SISPROBE, 2018. Marathon Passive Seismic Project, Meylan, France, 18p.
Executive summary: The records for the Marathon passive seismic project are of good quality and show usable ambient seismic noise especially in the period band [0.15 1.5]s (∼ 0.7-7 Hz) used for the tomography. The microseismic noise at high frequency is mostly coming the Great Lakes. At lower frequency, the noise comes from East-North-East direction (North Atlantic Ocean). The noise cross-correlations show essentially the fundamental mode of the Rayleigh waves travelling at an average velocity of ∼3 km/s. Due to the high velocity and the long wavelengths, we only used data from station pairs more than 900 m apart. It resulted in ∼1300 dispersion curves used for the inversion. The 3D S-wave velocity model is presented together with its uncertainties. The top of the gabbro intrusive slab is clearly imaged.
SISPROBE, 2017. Detection of old mine working for future infrastructure plan and development, 79th EAGE Conference & Exhibition 2017, Paris, France
As the demand for minerals are increasing, old mining areas are being revisited with the hope of further extracting resources. Some of these areas have been abandoned more than a century ago and as a result the exact location and the extent of the old mined out regions are unknown. Accurate knowledge of the mined out areas are important in order to plan infrastructure and future development. In other circumstances, mine operators are interested to detect remnant areas amongst older workings that have been hydrofilled so that these remnant areas can be mined. Seismic imaging methods have the potential to delineate these mined out areas from intact rock but have traditionally been too expensive to be used routinely. In this paper, we attempt to use a new passive method (called ambient noise surface wave tomography) to image old workings of an old Australian gold mine. Since the method does not require the use of a costly active source, it can be implemented at a fraction of the cost of a conventional active survey. The goal of the project was to see if the ambient seismic noise method could be used to identify old mine workings, mineral deposits, faults or shears and determine the thickness of the slag-heap.