The grey level co-occurrence matrix is a measure of the texture of an image. It describes how often different combinations of pixel brigthness values occur in an image. Based on this, several textural attributes can be calculated. In this work we developed a principal workflow for the calculation of these attributes. To decrease computational times we adapted calculation methods previously used for image classification of sea ice images. This workflow – including the enhanced calculation methods – is applied on two 3D seismic data sets from sedimentary basins. Different attributes and calculation parameters are tested to define channel systems and faults. The first tests show good results for the identification of both. Especially channel systems can clearly be identified. Additionaly, it is possible to directly extract channel-geobodies from the grey level co-occurrence matrix-based attributes.


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