基于保边滤波的断层似然属性在西湖凹陷复杂断裂识别中的应用

    Application of fault likelihood attribute based on edge-preserved filter in complex fault identification of Xihu Sag

    • 摘要: 西湖凹陷中央背斜带N构造区油气资源富集,但地质活动频繁,断层期次、交切关系复杂,同时,靶区地震资料信噪比低,目的层段反射杂乱,进一步影响断层精细刻画。本文利用非线性各向异性保边滤波方法去噪,克服传统线性滤波对断层边缘破坏问题,兼顾噪音压制与边界信息保护;通过对每个样点进行断层倾向和倾角扫描,依次计算相似系数和似然属性,选取最大的似然属性值作为最终结果,该方法较传统相干算法可更精细表征断层。实际资料应用表明:联合非线性各向异性保边滤波去噪与断层似然属性方法能够更好地压制随机噪音、保护断层边界信息,断层刻画精度更高,较好地落实了N构造区复杂断裂幕次精细刻画。

       

      Abstract: The N structure of the central anticlinal belt of Xihu Sag is rich in oil and gas resources, but it has undergone frequent geological activities with complex fault stages and cross-cutting relationship. In addition, the signal to noise ratio of seismic data in the target area is low, and the reflection of the target interval is chaotic, which further affects the fine description of faults. In this paper, nonlinear anisotropic edge-preserved filter technology was used to denoise and overcome the problem of traditional linear filter to fault edge, and considered the noise suppression and boundary information protection. The fault tendency and dip angle were scanned at each sample point, the similarity coefficient and likelihood attribute were calculated successively, and the maximum likelihood attribute value was selected as the final result. This method could characterize faults more accurately than the traditional coherence algorithm. The application of actual data shows that the combination of nonlinear anisotropic edge-preserved filter and fault likelihood attribute could better suppress random noise and protect fault boundary information, the fault characterization precision was greater, and could better characterize the complex fault stages in the N structure in more detail.

       

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