Ambient seismic noise analysis of LARGE-N data for mineral exploration in the Central Erzgebirge, Germany

Abstract

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.

Preface: State of the art in mineral exploration

“…In the last seismic exploration study compiled in this special issue, Ryberg et al (2022) carry out an ambient seismic noise tomographic survey to derive the 3D shear wave velocity model of the subsurface of the Geyer-Ehrenfriedersdorf mining district (Germany). This area hosts world-class magmatic hydrothermal ore deposits associated with the emplacement of the Geyer granite, containing important commodities such as Sn, W, In, Cu, Co, Bi, Sb and Au.…”

New Insights into the Internal Structures and Geotechnical Rock Properties of the Giant San Andrés Landslide, El Hierro Island, Spain

“…Additionally, often sparse vegetation and underground excavations (e.g., water galleries in the case of the Canary Islands) provide favorable conditions for reliable geological mapping [14]. A promising geophysical method potentially describing the rock environment properties to greater depths (up to hundreds of meters) is based on seismic ambient noise measurements [15,16], which are very small amplitude vibrations [17]. In recent years, ambient noise single seismic stations (H/V or HVSR, horizontal-to-vertical spectral ratio technique) and multiple seismic stations (seismic arrays) have been extensively adopted as they represent effective tools to characterize the elastic properties of the subsoil and detect seismic wave velocity changes with depth.…”

Fleet’s Geode: A Breakthrough Sensor for Real-Time Ambient Seismic Noise Tomography over DtS-IoT

“…The combination of ambient seismic noise tomography and nodal seismic stations has led to a so-called boom in boomless seismology in recent years [ 6 ]. The seismology community has successfully used ambient noise tomography and nodal seismic stations to image the subsurface to delineate mineral deposits, hydrocarbons, geothermal resources, fault zones, volcanoes and geotechnical structures [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ].…”