Estimation of Q and inverse Q filtering for prestack reflected PP-and converted PS-waves

Multi-component seismic exploration technology, combining reflected PP- and converted PS-waves, is an effective tool for solving complicated oil and gas exploration problems. The improvement of converted wave resolution is one of the key problems. The main factor affecting converted wave resolution is the absorption of seismic waves in overlying strata. In order to remove the effect of absorption on converted waves, inverse Q filtering is used to improve the resolution. In this paper, we present a method to estimate the S-wave Q values from prestack converted wave gathers. Furthermore, we extend a stable and effective poststack inverse Q filtering method to prestack data which uses wave field continuation along the ray path to compensate for attenuation in prestack common shot PP- and PS-waves. The results of theoretical modeling prove that the method of estimating the S-wave Q values has high precision. The results from synthetic and real data prove that the stable inverse Q filtering method can effectively improve the resolution of prestack PP- and PS-waves.

Interval Q inversion based on zero-offset VSP data and applications

In order to obtain stable interval Q factor, by analyzing the spectrum of monitoring wavelet and down-going wavelet of zero-offset VSP data and referring the spectrum expression of Ricker wavelet, we propose a new expression of source wavelet spectrum. Basing on the new expression, we present improved amplitude spectral fitting and spectral ratio methods for interval Q inversion based on zero-offset VSP data, and the sequence for processing the zero-offset VSP data. Subsequently, we apply the proposed methods to real zero-offset VSP data, and carry out prestack inverse Q filtering to zero-offset VSP data and surface seismic data for amplitude compensation with the estimated Q value.

Improve Q estimates with spectrum correction based on seismic wavelet estimation

Characterization of seismic attenuation,quantified by Q,is desirable for seismic processing and interpretation.For seismic reflection data,the coupling between seismic wavelets and the reflectivity sequences hinders their usage for Q estimation.Removing the influence of the reflectivity sequences in reflection data is called spectrum correction. In this paper,we propose a spectrum correction method for Q estimation based on wavelet estimation and then design an inverse Q filter.The method uses higher-order statistics of reflection seismic data for wavelet estimation,the estimated wavelet is then used for spectral correction.Two Q estimation methods are used here,namely the spectral-ratio and centroid frequency shift methods.We test the characteristics of both Q estimation methods under different parameters through a synthetic data experiment.Synthetic and real data examples have shown that reliable Q estimates can be obtained after spectrum correction;moreover, high frequency components are effectively recovered after inverse Q filtering.

A joint high-resolution processing method and its application for thin inter-beds

Seismic processing characterizing thickness and borders of thin inter-beds has gradually evolved fi＇om post-stack migration to pre-stack migration, and the latter considers both vertical and lateral resolutions. As the key processing methods for improving vertical and lateral resolution, conventional deconvolution and pre-stack time migration （PSTM） are not simply dominated by the estimation and compression of the wavelet because of its instability. Therefbre, considering the variations of wavelet frequency belbre, during and alter PSTM can obtain good common reflection point （CRP） gathers and imaging profiles of thin inter-beds. Based on the frequency characteristics of the wavelet before, during and after PSTM, a joint high-resolution processing method for thin inter-beds is proposed in this paper, including inverse Q filtering for high-frequency compensation before PSTM, optimum weighting Kirchhoff PSTM for preserving high-frequencies during PSTM, and wavelet harmonizer deconvolution tier consistent processing and frequency-band broadening after PSTM. An application to real data characterized by mudstone beds in the Oriente Basin proved that the joint high-resolution processing method is effective for determining the thickness and borders of thin inter-beds and is favorable for subsequent reservoir prediction and seismic inversions.