基于地震纹理属性的裂缝预测方法及应用

Fracture prediction method based on seismic texture attributeand its application

裂缝是主要的油气储存场所,准确识别裂缝对寻找油气具有重大意义。裂缝的地震响应特征可类比于图像的纹理。从纹理的图像处理角度出发,借助纹理分析方法可以对目标区域的裂缝进行识别。首先,对地震数据体进行不同级别的灰度映射,并选择不同的分析参数,如滑动窗口大小、计算方向等,利用灰度共生矩阵提取出多组纹理属性;然后,利用主成分分析方法对提取出的多组纹理属性进行二维可视化分析,从中优选出一组纹理属性,并计算其主成分;最后,利用模糊c均值聚类法对主成分进行聚类分析,并以概率的形式描述裂缝的分布特征。通过实例分析证实,该方法能够准确识别裂缝分布特征,提高裂缝识别的精准度。

Fractures are the main storage space for oil and gas,so accurate identification of fractures is of great significance for oil and gas exploration.The seismic response characteristics of fractures can be analogous to the texture of images.From the perspective of texture image processing,fractures in the target area can be identified by texture analysis method.Firstly,the seismic data volume was mapped to different levels of gray,and different analysis parameters were selected,such as sliding window size,calculation direction,etc.,and multiple groups of texture attributes were extracted by gray level co-occurrence matrix in this paper.Then,the principal component analysis method was used to carry out two-dimensional visual analysis on the extracted groups of texture attributes,from which a group of texture attributes were preferentially selected and their principal components were calculated.Finally,the fuzzy c-means clustering method was used to cluster the principal components,and the distribution characteristics of fractures were described in the form of probability.The example analysis shows that this method can accurately identify the characteristics of fracture distribution and improve the accuracy of fracture identification.