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Detection of regions of structural complexity within aeromagnetic data using image analysis

Mineral exploration requires selecting grounds where exploration is to be conducted. Ground selection and mineralisation targeting processes require identification of areas with specific geological settings. For exploration of Archaean lode gold deposits, crustal breaks are used as conduits for mineralising fluids and their structural associations such as crossings, junctions, and changes of orientations are closely associated with mineralisation. Aeromagnetic data represent magnetic response variations from the Earth's crust, and discontinuities in these data reveal crustal breaks, along with lithological boundaries and dykes that are important for understanding the local geology. This paper presents on-going image analysis research that aims to detect such characteristics within aeromagnetic data automatically, in order to provide an efficient and non-subjective analysis for gold prospectivity mapping. The proposed method automatically highlights the regions of high structural complexity within regional datasets. It firstly finds regions of magnetic discontinuity using a combination of texture analysis and bilateral symmetric feature detection, where line-like features representing high local magnetic variations are identified. Using skeletal structures of the identified regions of discontinuity it analyses structure associations to locate their intersections as well as to find orientation variations of neighbouring structures. Finally, by applying an accumulative Gaussian weighting, it generates heat maps that highlight the areas that are perceived to be prospective. A preliminary experiment was conducted using aeromagnetic data from the Yilgarn Craton in Western Australia and the regions selected by the proposed system are highly correlated with the known gold deposits in the area.