Abstarct: Abundant sedimentary structures and tectonic conditions constructive in Iran have an important role in the concentration of hydrocarbon resources and the various methods are used to identify these structures. Identify of smaller faults and fractures are possible only by the surface geological data. So indirect methods such as seismic method are used to identify these structures. Several uplift of mud volcanoes and gas and hydrocarbon are occurred in the study area in Golestan province. So faults and complex geological conditions have created. The detailed study of the place of main reservoirs has certain conditions; also fluid exhausted increase noise in the seismic data has increased. Seismic techniques identify faults with using seismic attributes which can be obtained more information from seismic data, But in most cases unable to provide a comprehensive model of regional fault lonely. So to achieve a more comprehensive version of fractures and faults of the study area, methods such as principal component analysis, is enough. Combination of attributes is created that enhance the quality of seismic section to identify better the faults. In this study, by using principal component analysis on seismic attributes, the main component with a high percentage of variance were prepared and prepared appropriate sections. The study on these sections, smaller fractures and faults were seen with better resolution. Although these images and sections diagnose faults well, but also these images in RGB color concept are increasing the resolution of fractures. Also to raise quality levels, attributes that have the optimal band combination of using statistical indicators were selected and according to Crosta. By applying principal components analysis on this attributes, images contain all the information were prepared. The resulting images have more detailed and more accurate than other methods in showing faults and fractures.