基于连通区域离散度的断层识别

    Fault Recognition Based on Connected Component Dispersion

    • 摘要: 针对地震剖面数据中有效层位信息与噪声混合分布,传统方法难以对地震断层进行识别的问题,提出了一种基于连通区域离散度的地震断层识别方法. 首先,基于八邻域连通对地震剖面二值图像中的连通区域进行标注并提取每一个连通区域的离散度等数字特征;然后,基于噪声和地震层位各自所属连通区域横向长度和离散度的不同对噪声进行去除;最后,利用地震层位所属连通区域的横向端点信息对地震断层进行识别并标注. 通过实验将所提方法与传统方法进行了对比,实验结果验证了所提方法的有效性和实用性.

       

      Abstract: To solve the problem that the traditional methods are difficult to detect the seismic fault in case of the effective seismic horizons in the section are mixed with noises, a fault recognition method based on connected component dispersion was proposed. First, the connected component in the binary seismic image was labeled out based on the eight neighbor connectivity and the digital dispersion and other characteristics of each connected component were extracted. Then, the noises were eliminated based on the horizontal length and dispersion difference between the noise and the connected component corresponding to the seismic horizons. Furthermore, the seismic faults were identified and labeled out based on the horizontal endpoints of the connected component corresponding to the seismic horizons. Finally, the algorithm was compared with the traditional ones through experiments, and the results validated the effectiveness and the practicability of the proposed algorithm.

       

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