The Research Of Seismic Texture Extraction Method And Analysis Of Influencing Factors

Texture is a common feature of image, which is presented on the surface ofobjects and can be observed by naked eyes. Compared with other features on theimage, texture feature is particular. There are different textures on different surfaceswith different features. Texture features can be extracted by mathematical meanseffectively, and can help to discriminate different images. Texture is widely usedbecause of its particular texture features in the image processing and patternrecognition.Strata can cause faults, cracks and other geological phenomena due to tectonicmovement, thus leaves the imprint of the change of geological time. These traces canbe regarded as texture from graphic. Geologists began to try to use image processingmethods to extract and analyze seismic texture in order to highlight its internalfeatures, which can identify faults or cracks effectively and provide a better basis tofind oil or gas.This article talks about statistical method, structural analysis method, signalprocessing method and modeling of texture analysis, and then one basic method isselected respectively for specific introduction.In the seismic texture attributes extraction process, first seismic texture featurewhich can be extracted from seismic texture attributes should be confirmed. And lastgray level co-occurrence matrix method, which is widely used to extract seismictexture attribute, is selected. Gray level co-occurrence matrix features are used tocharacterize geological features.Gray level co-occurrence matrix algorithm is realizedby C++program. The program not only needs to solve the selection of seismic textureattributes, which can be extracted by gray level co-occurrence matrix and the textureattributes is significant for seismic texture analysis, but also the confirmation of mostappropriate parameters for the region after the analysis and selection of important parameters in gray level co-occurrence. It is great importance to apply GLCM-basedthe seismic texture extraction methods in geological field. It can be widely used in therecognition of seismic sequence stratigraphy, faults, sedimentary bodies and buriedhill development zone and other aspects in geology.In this paper, the author adopts GLCM-based to extract seismic texture attributesand achieve its procedures. According to4texture attributes (energy, entropy, contrast,homogeneity,) the author analyzes different geological characterization ability. FuzzyK means clustering the unsupervised classification method in pattern recognition toextract effective classification of seismic texture attributes is used. Finally accurateidentification of geologic target is realized. This thesis is a case study on Liaohe OilField Dynamic Tuen Shen257block of seismic data. The author makes algorithmtesting, selects the most appropriate gray level co-occurrence matrix parameters fromthe seismic data, and gets satisfactory results finally.