自适应分段的时变子波估计方法

针对目前时变子波估计中忽略地震记录的非平稳特性导致子波估计不准的问题,提出了一种基于自适应分段的时变子波估计方法.根据自适应分子分解法基本原理,自适应分段以二次谱法替代原有的多项式法拟合子波振幅谱,有效提高了自适应分子窗的寻优精度;采用使时变子波振幅谱相似度最大的方法确定最优的时窗函数分段,实现自适应分子窗的合理划分,进而以傅里叶反变换实现时变子波估计.通过数据仿真和实际地震数据处理等验证了该方法在子波估计中的有效性和适用性.

Time-variant wavelet estimation based on adaptive segmentation

Most current wavelet extraction methods based on conventional convolution model do not take the nonstationarity of seismic data into considerations, so the extracted wavelet is not accurate. Therefore we propose in this paper a time-variant wavelet estimation method based on adaptive segmentation. First, according to the principle of the adaptive molecular decomposition, the secondary spectrum simulation replaces the fitted wavelet spectrum of the polynomial method to greatly improve the optimization accuracy of adaptive molecular windows. Then, an approach for similarity maximum of time-variant wavelet spectrum is chosen to determine optimum window segmentation. Finally the time-variant wavelet is obtained with inverse Fourier transform after adaptive molecular windows are segmented. Simulation and real seismic data tests show that the proposed method is suitable for time-variant wavelet estimation.