小波包变换叠前地震信号研究

叠前地震资料是多种波的复合体，为了提取有效波，必需消除主要的干扰波，如面波，高频随机干扰波，一般的去噪方法有；一维滤波，滤波，变换，f-x预测等，但它们都侧重于考虑某一方面的单一特性或某种条件假设，这些方法具有一定的局限性，小波包变换是一种时频分析的方法，它对地震资料进行时频精细划分优于小波变换，与传统的Fourier变换相比，它能刻画出具有相同频率的有效波与干扰波在时间-空间域的分布，经过小波包对叠前资料分解，可分离出面波，高频随机干扰等，然后再经过波波包重构，可有效地剔除干扰，且对有效波的伤害较少，经实际资料验证，小波包变换，确实是一个十分有效的去噪方法。

Study on Pre-Stacking Seismic Signals for Wavelet Packet

There are usually different noises in seismic data before stacking.In order to pick-up effectual wave,we must remove noise waves such as surface wave and random noise with high frequency.The normal methods include:1D filter,f-x filter,t-p transform,f-x prediction,etc.However,these methods have limitations that they only particular emphasis on a single characteristic of surface wave or are based on some hypothesis.Wavelet packet is a time-frequency analytical method,and can be better of dividing the seismic data in detail than wavelet transform.It can describe the distribution of effectual wave and noise wave in time-space field at same frequency,comparing with traditional Fourier transform.By decomposing seismic data before stacking with wavelet packet,separate surface-wave and random noise of high frequency from seismic data.After processing wavelet packet reconstruction,we can eliminate noise-wave and al-low fewer damage of effectual wave.Through validating real data,wavelet packet is good for removing noise.