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.
Check out our project log on Research Gate: https://www.researchgate.net/project/PACIFIC-H2020
Executive summary: This deliverable gathers risks related to safety or environmental issues relevant for PACIFIC activities. For each type of issue, the risks/hazards are listed with their score before and after mitigation and the corresponding control measures. A safe working procedure is also described. This database will serve as reference for the ESMC – Environmental and Safety Risk Management Committee – for follow-up during the course of the project.
Download the PACIFIC project presentation https://www.pacific-h2020.eu/wp-content/uploads/PACIFIC-Project-presentation.pdf
Executive summary: A key goal of the PACIFIC project is to develop methodologies for the extraction of body waves from passive seismic data, for use in the environmentally sustainable environments. Recovering body waves from ambient noise data has proved to be challenging as they are usually weak and ambient noise fields are rich in surface waves. Here we propose and test a method, based on the Radon Transformation, that helps suppress surface waves and enhance reflected body waves. The method exploits the ‘moveout’ differences between reflected body (hyperbolic) and surface waves (linear) and is tested on synthetic 2D & 3D model data prior to its application to ambient noise field data. We refer to it as Radon Correlation. Synthetic tests are very encouraging, showing clear body wave recovery that cannot be seen in raw cross-correlated data. Using these synthetics to have a choice of parameters, we then move to field passive data from the Marathon site within PACIFIC. We generate virtual shot gathers by applying Radon Correlation to single virtual sources into a linear array of receivers. Again, results are very encouraging with clear reflected body wave recovery from the ambient noise data and determined by clear hyperbolic arrivals on the virtual shot gathers. There is a hint that using time windows that contain active blast seismic coda possibly further enhances body wave recovery. Finally, velocity analysis on these virtual shot gathers leads to a P-wave velocity model that compares well with models derived from surface wave dispersion analysis of the same ambient noise data. However, these models are not currently publicly available and hence are not shown here, in this report.
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