基于反褶积广义S变换的地震频谱成像方法研究

当薄互层较发育时,利用地震资料对储层的含油气性进行预测存在较大的困难。因此,发展高精度的时频分析方法并将其应用于储层内的烃类检测具有重要意义。提出了基于反褶积广义S变换的新时频分析方法;该方法将信号的广义S变换谱与窗函数Wigner-Ville分布进行二维反褶积,可得到信号Wigner-Ville分布。通过数值模拟结果可知,该方法与传统的时频分析方法相比,不仅克服了传统时频方法采用固定时窗分析信号的局限,并且具有更高的时频分辨率。三维实际资料处理结果表明,相对于传统时频方法,该方法适用于非平稳的地震信号分析;在薄储层预测方面更具优势,进行烃类检测的可靠性也较高。

Seismic Spectral Imaging Method based on deconvolutive Generalized S Transform

When the thin mutual layer is relatively developed, it is difficult to predict the hydrocarbon bearing reservoir by seismic data. Therefore, it is significant to develop a high precision time frequency analysis method and apply it to the hydrocarbon detection in the reservoir. A new time-frequency analysis method of deconvolution based on generalized S transform is proposed, the method of the generalized S transform spectrum and window function Wigner-Ville distribution of signal two-dimensional deconvolution signal can be obtained with Wigner-Ville distribution. The numerical simulation results show that the proposed method not only overcomes the limitation of the traditional time-frequency analysis method, but also overcomes the limitation of the traditional time-frequency analysis method, and has higher time frequency resolution. The actual 3D data processing results show that compared with the traditional time-frequency method, this method is suitable for non-stationary seismic signal analysis in the prediction of thin reservoirs with more advantages, the reliability of hydrocarbon detection is higher.