Geolithological mapping of carbonate system deposits for hydrocarbon exploration using hyperspectral imagery

Hyperspectral remote sensing can support exploration activities helping in the recognition of lithologycal outcrops over extended areas. This is mainly due to the nature of the mineral reflectance spectra which feature very narrow absorption peaks, therefore requiring hyperspectral sensors to be assessed. In this work, the capabilities for geolithology recognition of aerial hyperspectral data have been tested to map outcrops in an Alpine carbonates test basin, located in the North-Eastern part of Italy. Two hyperspectral datasets, from MIVIS and SASI sensors, have been classified to retrieve the geolithological map of the test basin. The classification procedure was based on a decision tree approach, in order to combine different spectral and morphological features, in a flexible, robust and scalable solution. Despite the geological complexity of the study area (Alpine environment, spread vegetation cover, strong presence of shadow areas and presence of transitional geologic formations) the results, as compared to reference geological maps, prove satisfactory mapping capabilities, particularly for carbonatic rocks. In fact, the use of aerial hyperspectral data not only allows their accurate detection, but also the distinction between dolostones and limestones. The main classification issues are related to the outcrops' extent which, in a such lithology-fragmented area, avoids the detection of many small outcrops.