Locating skarns with magnetic survey data, Geyer, Erzgebirge: optimizing data acquisition procedures

Abstract

Magnetic data can be acquired from a number of different platforms (e.g., ground, drone, helicopter) using a variety of sensors (e.g., caesium vapour‐type optically pumped magnetometers, fluxgate, superconducting quantum interference devices) with different flight line configurations. To detect a magnetic anomaly associated with a mineral commodity that is not exposed but is thought to be associated with the anomalous magnetic mineral content, it is necessary to optimize the survey parameters through a complete data integration process. Prior petrophysical measurements provide insight into the physical contrast that might be expected between adjacent lithologic units and between the ore zone and the encompassing lithology. Oriented rock samples provide access to magnetic remanence data through palaeomagnetic laboratory measurements. Knowing the typical morphology of the ore zone one can compute a forward model of the expected anomalous response and determine which combination of survey parameters provides the highest probability of detecting the commodity being sought. In this study, we analyse magnetic patterns associated with thin dipping skarn bodies from the Geyer mining district in Erzgebirge, Germany. Petrophysical measurements indicate that the skarns are more magnetic than the surrounding host rock. Partially oriented samples from a bore core record a Variscan age metamorphic remanence. Forward modelling indicates that clusters of skarn bodies are required to produce a reliably detectable magnetic signal. Ground, or low elevation drone surveys are needed to detect these anomalies with standard scalar‐type optically pumped magnetometer or fluxgate magnetic surveys. The enhanced spatial resolution and long‐wavelength rejection of a superconducting quantum interference device based full‐tensor magnetic gradiometer provide an improvement over optically pumped magnetometers for an aircraft‐based survey platform.