Grey level co-occurrence matrix and its application to seismic data

Christoph Georg Eichkitz, John Davies, Johannes Amtmann, Marcellus Gregor Schreilechner and Paul de Groot demonstrate how grey level co-occurrence matrix can be adapted to work on 3D imaging of seismic data. Texture analysis is the extraction of textural features from images (Tuceryan and Jain, 1998). The meaning of texture varies, depending on the area of science in which it is used. In general, texture refers to the physical character of an object or the appearance of an image. In image analysis, texture is defined as a function of the spatial variation in intensities of pixels (Tuceryan and Jain, 1998). Seismic texture refers to the magnitude and variability of neighbouring amplitudes at sample locations and is physically related to the distribution of scattering objects (geological texture) within a small volume at the corresponding subsurface location (Gao, 2008). Four principal methods have been developed for the analysis of seismic texture (Figure 1). These are texture classification, segmentation, synthesis, and shape.