Quality factor Q estimation based on S transform andvariational method
XU Li'nan1, GAO Jinghuai1, YANG Yang1, GAO Zhaoqi1, WANG Qian2
1. School of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China; 2. School of Mathematics and Statistics, Hubei University of Arts and Science, Xiangyang, Hubei 441053, China
Abstract：Quality factor Q is an important parameter to quantitatively describe the viscoelastic attenuation. Accurate Q estimation is beneficial to reservoir identification and hydrocarbon detection. It can also be used for inverse Q filtering to improve the resolution of seismic data. The traditional Q estimation methods include logarithmic spectrum ratio (LSR), center frequency shift (CFS), and peak frequency shift (PFS), etc. LSR has poor noise immunity. Both CFS and PFS depend on the type of seismic wavelet. In response to these problems, this paper proposes a robust Q estimation method based on the S transform and variational method. Firstly, by studying the nonstationary convolution model, we derived the approximate representation of nonstationary seismic data in the S domain. Seco-ndly, on the basis of approximate representation, the objective function of quality factor Q and seismic wavelet is established and minimized based on the variational method, thereby obtaining the expression of Q estimation. Finally, we designed an adaptive selection scheme of an integral interval to improve the accuracy and noise resistance of the method. This scheme can automatically calculate the frequency parameters of the integration area based on the time-frequency spectrum of seismic data. Model examples demonstrate that the proposed method does not rely on the wavelet type and the length of the window function and shows good robustness to noise. The real data further verifies the effectiveness of the method in Q estimation.
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