An analysis of seismic texture attribute based on GLCM

摘要

This paper applies for the gray level co-occurrence matrix(GLCM) algorithm to characterize seismic texture attributes. For seismic data with high quality, firstly, the algorithm calculated gray level co-occurrence matrix of each sample point, then extracted secondary statistics of the gray level co-occurrence matrix, namely homogeneity, contrast, energy and entropy, because of the characteristics of gray level co-occurrence matrix and the impact of the stratigraphic dip model, direction-sensitive of the algorithm, this paper introduces the method of dip scanning, searches each sample point according to dip, to build the gray level co-occurrence matrix. Thus based on the texture attribute algorithm of gray level co-occurrence matrix can better adapt the stratum information. Finally, we make use of the algorithm for real seismic data of the study area F11 upper sand group. The actual data shows that the texture attribute of algorithm can do better for detection of faults and rivers, and achieve better results.