Abstract. Ambient seismic noise tomography is a novel, low-impact
method for investigating the earth's structure. Although most passive seismic
studies focus on structures on crustal scales, there are only a few examples
of this technique being applied in a mineral exploration context. In this
study, we performed an ambient seismic experiment to ascertain the
relationship between the shallow shear wave velocity and mineralized zones
in the Erzgebirge in Germany, one of the most important metal provinces in
Europe. Late Variscan mineralized greisen and veins occurring in the
Geyer-Ehrenfriedersdorf mining district of the Central Erzgebirge were mined
from medieval times until the end of the 19th century. These occurrences
represent a significant resource for commodities of high economic
importance, such as tin, tungsten, zinc, indium, bismuth and lithium. Based
on ambient noise data from a dense “LARGE-N” network comprising 400
low-power, short-period seismic stations, we applied an innovative
tomographic inversion technique based on Bayesian statistics
(transdimensional, hierarchical Monte Carlo search with Markov Chains using
a Metropolis/Hastings sampler) to derive a three-dimensional shear wave
velocity model. An auxiliary 3D airborne time-domain electromagnetic dataset
is used to provide additional insight into the subsurface architecture of
the area. The velocity model shows distinct anomalies down to approximately
500 m depth that correspond to known geological features of the study area,
such as (a) gneiss intercalations in the mica schist-dominated host rock,
imaged by a SW–NE striking low-velocity zone with a moderately steep
northerly dip, and (b) a NW-trending strike-slip fault, imaged as a
subvertical linear zone cross-cutting and offsetting this low-velocity
domain. Similar to the velocity data, the electromagnetic data exhibit
north-dipping (high-conductivity) structures in the mica schists,
corresponding to the strike and dip of the predominant metamorphic fabric.
An unsupervised classification performed on the bivariate 3D dataset yielded
nine spatially coherent classes, one of which shows a high correspondence with
drilled greisen occurrences in the roof zone of a granite pluton. The
relatively high mean shear velocity and resistivity values of this class
could be explained by changes in density and composition during greisen
formation, as observed in other areas of the Erzgebirge. Our study
demonstrates the great potential of the cost-efficient and low-impact
ambient noise technology for mineral exploration, especially when combined
with other independent geophysical datasets.