Texture attributes originate from image processing where they were developed to capture the roughness or smoothness of an image by describing the relationship between pixels (Haralick et al., 1973). In seismic interpretation texture attributes are used in seismic facies analysis and to highlight geo-morphological features (e.g. Vinther et al., 1996; Gao, , 2008, 2009, 2011; West et al., 2002; Chopra and Alexeev,, 2006, ; Yenugu et al., 2010; de Matos et al., 2011, de Groot et al., 2013).

Texture attributes are based on the Grey Level Co-occurrence Matrix (GLCM), a 2D matrix of N x N dimensions representing the amplitude values of the reference pixel versus the amplitudes of the neighbouring pixel. The original GLCM calculation was developed for 2D images. The matrix is filled by comparing each amplitude in the input area with its direct neighbour and increasing the occurrence of the corresponding matrix cell. This is repeated for all amplitude pairs in the input area which are then converted into probabilities. The GLCM thus captures how probable it is to find pairs of neighbouring amplitudes in the area around the evaluation point.

Three groups of texture attributes are computed from the GLCM: Contrast (contrast, dissimilarity & homogeneity) where measurements are calculated through the use of weights related to the distance from the GLCM diagonal; Orderliness (ASM, energy & entropy) where interpreters measure how regular the pixel values are within the window; and Statistics (mean, variance & correlation) that are derived from the GLCM. In each group, the attributes are highly correlated.