基于构造导向滤波的分频曲率技术在断层精细识别中的应用
Application of Frequency Division Curvature Technology Based on Structural Guided Filtering in Fine Fault Identification

塔里木H油田油源及输导体系不明确，制约了滚动评价的进展，高精度精细断层识别对H油田滚动勘探及开发部署具有重要意义。H油田砂岩储层具有埋藏深、地震资料信噪比低等特点，无法有效进行断层的精细识别，需要提升微小断裂的地震识别能力。文章提出一种实现断层精细刻画的检测流程，首先对原始地震数据进行构造导向滤波，沿同相轴方向压制随机噪声，提高信噪比；然后利用小波变换对滤波后的地震数据进行分频处理；最后优选单频数据体进行曲率运算得到高精度的断层检测数据体。与原有曲率资料进行对比分析，结果表明，该方法能够有效提高塔里木H油田的断层识别精度，为滚动开发提供参考。
The oil source and transmission system of Tarim H oilfield are unclear, which restricts the progress of rolling evaluation. The high precision fine fault identification is of great significance to the rolling exploration and development deployment of H oilfield. The sandstone reservoir of H oilfield has the characteristics of deep burial and low signal-to-noise ratio of seismic data, which cannot effectively identify faults without improving the seismic identification ability of small faults. In this paper, a detection process is proposed to realize the fine characterization of faults. First, the original seismic data is structure-oriented and filtered, and the random noise is suppressed along the same phase axis to improve the signal-to-noise ratio; Then, the wavelet transform is used to process the filtered seismic data by frequency division; Finally, the single frequency data body is preferred to calculate high precision fault detection data body. By comparison with the original curvature data, the results show that this method can effectively improve the fault identification accuracy of the oil field in Tarim H, and provide a reference for rolling development.