Abstarct: Geophysical methods especially reflection seismology are the best methods for exploration of subsurface structures of the earth. Salt domes are the geological subsurface structures which are one of the most important hydrocarbon traps and underground hydrocarbon storage. These structures are useful for isolating nuclear waste, dissolution mining methods, underground structures and compressed air tank. Seismic attributes are very useful tools in seismic data interpretation and characterization of geological features which reveal hidden information in reflection seismic data. Grey level co-occurrence matrix (GLCM) baxsed seismic texture attributes are the important group of seismic attributes which used for salt domes identification. Grey level co-occurrence matrix is an image processing tool for extraction of texture feature of an image. In this method, the histological characteristics of a pixel in image determined by value of its neighboring pixels. We consider the seismic section as 2D image to compute the GLCM baxsed seismic texture attributes. Due to texture differences of salt domes with surrounding structures, the texture attributes can distinguish between them. The efficiency of the GLCM baxsed seismic attributes can be improved by dip guided calculation of the attributes. In this thesis, the dip of geological structures has been considered in the calculation of the attributes. In this way, we improve the estimation of salt dome lateral boundaries. In the next step, we introduce the suitable texture attributes to support vector machine which is a useful classification to detect the baxse of salt domes