Ambient noise surface wave tomography (ANSWT) is an environmentally friendly and cost-effective technique for subsurface imaging. In this study, we used natural (low-frequency) and anthropogenic (high-frequency) noise sources to map the velocity structure of the Marathon Cu-PGE deposit (Ontario, Canada) to a depth of 1 km. The Marathon deposit is a circular (ø = 25 km) alkaline intrusion comprising gabbros at the rim and an overlying series of syenites in the centre. Cu-PGE mineralisation is hosted by gabbros close to the inward-dipping footwall of the intrusion. The country rocks are Archaean volcanic breccias that are seismically slower than the gabbros, and similar in velocity to the syenites. We used ANSWT to image the footwall contact that controls the location of the mineralisation.

An array of 1024 vertical-component receivers were deployed for 30 days to record ambient noise required for surface wave analysis. Two overlapping grids were used: a 200 m x 6040 m dense array with node spacing of 50 m, and a 2500 m x 4000 m sparse array with node spacing of 150 m. The signal was down-sampled to 50 Hz, divided into segments of 30 minutes, cross-correlated and stacked. Surface wave analysis was conducted over the dense array and the sparse array data. We considered the fundamental mode of Rayleigh wave propagation for our frequency-wavenumber (F-K) analysis and focused on the phase velocity variation in the high-frequency ambient noise signal (up to 22 Hz). We reconstructed the shallow structure with progressively increased resolution using surface wave dispersion curves extracted from receiver arrays divided into segments of variable lengths. Several average dispersion curves were computed from individual dispersion curves belonging to different seismic lines. Each average dispersion curve was inverted to obtain S-wave velocity models using an McMC transdimensional Bayesian approach.

The tomographic images reveal a shallow high-velocity anomaly, which we interpret as being related to the gabbro intrusion that hosts the mineralization. The large-wavelength structures in the S-wave velocity models are relatively consistent with the geological structures inferred from surface mapping and drill core data. These results show that the ANSWT, focused on the high-frequency signal provided by anthropogenic noise sources, is an efficient technique for imaging “shallow" (1 km depth) geological structures in a mineral exploration context.

At the invitation of Dr. Andrew Schaeffer (Geological Survey of Canada, Natural Resources Canada), Dr. François Lavoué (UGA) presented the PACIFIC work on the use of seismic signals generated by trains for passive seismic imaging and monitoring on May 5th, 2021. The presentation provided an overview of the activities carried out within the framework of both the PACIFIC and FaultScan EU-funded projects.

The presentation was attended by around 40 people. Technical questions revolved around the parameters controlling signal amplitude, and a more general debate took place on the merits of excluding signals generated by trains from "classic" ambient noise datasets, as is done for earthquakes.

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

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).

The accepted version and the supplementary material can be downloaded as a compressed file from this webpage.

The link to the published version is provided below as well.

Sometimes noise is incredibly helpful.

By Rahul Rao, Popular Science (January 28, 2021)

For the full article, please visit How trains can help scientists study what's underground | Popular Science (popsci.com)

Click here to download the press release (Pdf format) announcing the online event co-organised by INFACT, PACIFIC and the NHM on December 3-4, 2020.

Technique now possible due to improvements in lithium batteries which power monitoring equipment

Article in the Canadian press by Jeff Walters · CBC News · Posted: Jun 12, 2019 1:28 PM ET  https://www.cbc.ca/news/canada/thunder-bay/thunder-bay-pacific-new-exploration-1.5172168 

Download PACIFIC first press release (July 2018): PACIFIC first press release

 Charlie Beard's presentation can be viewed on the link https://www.youtube.com/watch?v=g_qdwQGHNhs 

Executive summary: The Winter School on Sustainable Mineral Exploration was jointly organized by two European projects—PACIFIC and INFACT. The event was held at the International Campus of Andalusia in Huelva, Spain, between the 9th and 12th March 2020. The Winter School was divided in 3 lecture sessions, 1 practical session, and 2 visits to mining sites. The main goal of this school was to present the techniques and knowledge on sustainable mineral exploration that have been developed within the INFACT and PACIFIC projects. The school targeted an audience of European master students, PhDs and post-doctoral researchers. A total of 40 students, including 15 from the University of Huelva, physically attended the school. An additional 13 students participated in parts of the school via video conference, since unfortunately due to travel restrictions stemming from the COVID-19 pandemic those 13 students were unable to attend in person. Videoconferencing was a last-minute adaptation made by the Winter School to allow for the participation of individuals under travel bans, quarantine, or other restrictions. Students (both physical and remote attendees) came from 13 countries. The results of the anonymous survey conducted at the end of the school reveal that the event was a success, despite the ongoing COVID-19 crisis.