The Study Of Texture Attributes Extracting And Sedimentary Facies Using Gray Level Co-occurrence Matrix

Currently, the 3D seismic attribute has been widely used in seismic interpretation, mainly used for the geological structure and geological interpretation, and the identification of lithology and pore fluid, reservoir characterization. With the rapid development of high-speed digital computers, the application of computer to digital seismic records is a variety of processing and interpretation. Many kinds of seismic attributes has been developed, the root mean square amplitude attribute, the commonly used frequency attribute, coherence attribute, the AVO attribute, the properties of wave impedance and so on. A large number of attributes is mainly used for reservoir prediction and reservoir characterization. These properties are sensitive to fluid of lithology, some are sensitive to the fault, some are sensitive to channel sand body. Three dimensional seismic attributes can help geophysical and geological engineers 3-D visualization interpretation, improve the interpretation accuracy and efficiency.First, this article introduces the concept of texture features, explains what is the analysis method of the four kinds of texture feature in the study of texture analysis, because seismic texture attributes compared with other Seismic attributes, it has its unique properties, so the extraction of seismic texture attributes is particularly important in seismic texture attributes analysis work, many methods of texture feature extraction, this article introduces three kinds of extraction methods, and compares the three methods have their own advantages and disadvantages, this paper finally chooses the property of gray level co-occurrence matrix extraction method based on.The traditional C1 algorithm (refers to the first generation coherence algorithm) is to calculate the seismic coherence along the line direction and road based on statistical correlation theory. In this article, we present a method of seismic attribute. It is a seismic texture coherence algorithm. From the texture of the processing technology, the proposed algorithm not only considers the seismic data along the line, the direction of the road, and contains a coherent response characteristics, and line number, road, in perspective of the direction of the coherent information, make full use of seismic coherence information in 4 directions. And, the application of texture processing technology to the traditional C1 algorithm considering the coherence of adjacent two or three between, extended to multi-channel coherent; This article has also carried on the analysis to the texture attribute parameter, through the response of texture characteristics to the different sections under different parameters, discussed the influence of different parameter regarding the texture attribute resolution. The treatment effect of the three dimensional data volume shows that, the treatment effect the horizontal resolution, the method has high, can identify the fault and sand boundary effectively. Finally Huan 2 block is selected based on tectonic and sedimentary data of the study of sedimentary facies of four sections with seismic attributes, good results have been achieved.