基于F-K域和Curvelet-中值滤波联合去噪的混采数据分离方法

由于炮分离过程会不可避免地损失部分有效信息,为解决这一问题,笔者建立模型试验,将混采数据转至频率域进行F-K滤波预处理,在保护地震同相轴的同时压制大部分混合噪声;并变换回时间域共偏移距道集进行小时窗中值滤波,同时设计迭代公式在共检波点道集进行Curvelet阈值迭代去噪;通过不断优化得到最后分离结果。模拟数据和实际数据处理结果证明:经本文方法分离后的单震源记录清晰,具有较好的实际应用价值。

Blended acquisition data separation method based on F-K domain and Curvelet-median filter joint denoising

Shot separation process will inevitably lose some useful information, in order to solve this problem, the authors set up model experiments, which transformed blended acquisition data into frequency domain common offset gathers for F-K filter pre-processing, and suppressed most blended noises in the process of preserving seismic event. The authors then transformed the data to time domain common offset gathers for small window median filter, and designed iteration formula to undertake Curvelet threshold iteration denoising for common receiver point gathers. Separation results were finally obtained by constant iterations. Both simulated synthetic and field data certify that the deblended single shot record processed by this method is clear, and has good practical application value.