叠前中值滤波

Prestack mid-value filtering

中值滤波是一种特殊的非线性平滑滤波。广泛用于数字图像处理等领域,在地震资料叠前处理中使用中值滤波,可以起到剔除野值和提高信噪比的作用。由于叠前资料的数据量很大,因此叠前中值滤波的计算效率是实用与否的关键因素。本文中的算法充分利用了中值滤波的特点,使计算效率大为提高。实际数据试验表明,叠前中值滤波在自动剔除野值和不正常道、提高叠前资料的信噪比以及消除面波干扰三个方面都有较好的效果。采用高通滤波消除横向相干的低频干扰后,中值滤波的效果会更好。

Mid-value filtering is a specific nonlinear smoothing filtering,and widely used in graphic processing,etc. Mid-value filtering before stack of seismic data can remove wild value(inconceivable particular big value)and improve signalnoise ratio. In view of big data volume before stack, computation efficiency of mid-value filtering is critical to its feasibility. The algorithm used here is sufficiently based on the properties of mid-value filtering,so that the computation efficiency is greatly improved. It is experimentally shown that prestack mid-value filtering can quite well eliminate wild value,abnormal traces as well as surface waves, and raise signal-noise ratio. After lateral low frequency noises are removed by high pass filtering,mid-value filtering works better.