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一般地,把速度滤波器用于叠前地震数据可压制长周期的多次波,但是它们也能损坏一次波的振幅。由于近偏移距地区道集数据的一次波和多次波之间的视速度差异可被忽略,速度滤波器将在这些地区失效,并且往往会消去或畸变一次波的信号。通常解决这一问题的方法是切除或删除近偏移距的数据,但这对低覆盖次数的地震数据是不利的。在本文中,我们导出一种滤波器能解决这一问题。它对一次波和多次波之间的平均视速度差而不是瞬时视速度差发生响应。这种滤波器叫做局部相干滤波器。它实际上是一有限差分算子,其步长等于空间预测距离。在局部相干滤波器小的应用时窗内,经动校之后的多次波是可预测的,而校正过量的一次波是不可预测的,其差分算子的步长大小使滤波器有能力区别速度滤波器所不能区分的一个数据集范围内一次波和长周期的多次波。本文在理论数据和实际数据应用上将局部相干滤波器与f-k滤波器作了对比,结果证明,前者更有效地压制了长周期多次波,而且不使一次反射发生畸变。
In general, using velocity filters for pre-stack seismic data can suppress long-period multiples, but they can also damage the amplitude of the primary. Since the difference in apparent velocity between the primary and the multiples of the gathers data for the near-offset region can be neglected, the velocity filter will fail in these regions and tend to cancel or distort the primary signals. A common solution to this problem is to remove or delete data at near offsets, but this is detrimental to low overlay seismic data. In this article, we derive a filter that solves this problem. It responds to the average apparent velocity difference between primary and multiple waves rather than the instantaneous apparent velocity difference. This filter is called a local coherent filter. It is actually a finite difference operator with a step size equal to the spatial prediction distance. In the small application window of the local coherence filter, the multiples after the dynamic calibration are predictable, and the first correction of the excess wave is unpredictable. The step size of the differential operator makes the filter have the ability to distinguish The speed filter can not distinguish between multiple primary and long period multiples within a data set. In this paper, we compare the local coherent filter with the f-k filter in both theoretical data and real data. The results show that the former suppress the long period multiples more effectively without distorting the primary reflection.