TV-L^1分解模型下的地震图像增强方法研究

Enhancement of seismic image based on seismic data decomposition by the TV-L^1 model

地震图像增强是指按特定的需要采用特定方法突出图像中的某些信息,同时削弱或去除无关信息,或将原图转换成一种更适合人或机器处理的形式的图像处理方法,其设计与其应用的目的密切相关,其宗旨是在不增加数据的内在信息含量的基础上,增加所选择特征的动态范围,以使其容易被检测到.本文提出一种针对地震纹理的地震图像增强方法.首先根据地震数据TV-L^1分解模型,把地震图像信息分解为结构与纹理分量,其中结构分量为几何形状较为明确的平滑区域,通常为低频信号部分;纹理分量则由地震纹理信号和噪声所组成,分别对应高频信号以及随机噪声.最后结合基于偏微分方程的图像质量改善算法分别对结构和纹理分量进行加强,其结果提高了地震图像的空间分辨率.

Audio magnetotelluric（ AMT） sounding is a fast,economical and topographically applicable electromagnetic method in complicated areas,which has great potential in coal-bed methane（ CBM） exploration. In this paper, three coal-bed methane reservoir patterns are presented in the southern Qinshui Bain. In order to meet the requirements of the AMT sounding,geo-electrical models with objective conductive and resistive layers embedded are designed. Two-dimensional（ 2D） inversion results of these models in the TE,TM and TETM modes reveal that the three-dimensional galvanic anomalies cause distortion effects in the two-dimensional interpretation. In contrast,3D inversion results not only depict the near-surface anomalies,but also give a more accurate distribution of objective thin conductive layers. However, 3D inversion is incapable of identifying objective thin high resistive layers. Only if the electrical constraints are imposed on the starting / priori models,the 3D inversion results would be obviously improved. In a word,the 3D inversion of thin low resistive layers is the optimum choice for practical exploration. In the Hudi block of southern Qinshui Basin,two 3D inversion section maps were obtained using the AMT method. The objective low resistive water-enrichment layers are extracted,and the status of coal-bed methane reservoirs are fully explored according to the deducted reservoir patterns and other known information. The interpretation results are quite consistent with the actual circumstances. All the above strongly demonstrate that the three-dimensional AMT inversion of thin low resistive layers gains prominence in the CBM exploration,and has great potential in monitoring CBM reservoirs and other underground resources.