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 exp...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.展开更多
Highly precise acoustic impedance inversion is a key technology for pre-drilling prediction by VSP data. In this paper, based on the facts that VSP data has high resolution, high signal to noise ratio, and the downgoi...Highly precise acoustic impedance inversion is a key technology for pre-drilling prediction by VSP data. In this paper, based on the facts that VSP data has high resolution, high signal to noise ratio, and the downgoing and upgoing waves can be accurately separated, we propose a method of predicting the impedance below the borehole in front of the bit using VSP data. First, the method of nonlinear iterative inversion is adopted to invert for impedance using the VSP corridor stack. Then, by modifying the damping factor in the iteration and using the preconditioned conjugate gradient method to solve the equations, the stability and convergence of the inversion results can be enhanced. The results of theoretical models and actual data demonstrate that the method is effective for pre-drilling prediction using VSP data.展开更多
The goals of this study were to examine factors influencing Q inversion and to provide references for practical application.Three different methods for inverting Q values with VSP data were explored,including centroid...The goals of this study were to examine factors influencing Q inversion and to provide references for practical application.Three different methods for inverting Q values with VSP data were explored,including centroid frequency shift(CFS),spectral ratio(SR),and amplitude attenuation(AA).Comparison between the CFS and the other two methods was conducted on frequency band widths and low attenuation,wavefield components,interface interference,and thin layers.Results from several sets of VSP modeling data indicated that the CFS method is more stable and accurate for dealing with thin and high Q layers.Frequency band width,especially the presence of high frequencies,influences the inversion effect of all three methods.The wider the band,the better the results.Q inversion from downgoing wavefield was very similar to that of the upgoing wavefield.The CFS method had fewer outliers or skip values from the full wavefield than the other two methods.Moreover,the applications to Q inversion for the set of field VSP data demonstrated that the Q curves from the CFS method coincided with the geological interpretations better than the Q curves of the other methods.Meanwhile,inverse Q filtering shifted the frequency component from 25 Hz to 35 Hz.The results demonstrated that the Q curve is more sensitive to geological horizons than velocity.展开更多
基金sponsored by the National Nature Science Foundation of China(Nos.41174114 and 41274128)
文摘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.
文摘Highly precise acoustic impedance inversion is a key technology for pre-drilling prediction by VSP data. In this paper, based on the facts that VSP data has high resolution, high signal to noise ratio, and the downgoing and upgoing waves can be accurately separated, we propose a method of predicting the impedance below the borehole in front of the bit using VSP data. First, the method of nonlinear iterative inversion is adopted to invert for impedance using the VSP corridor stack. Then, by modifying the damping factor in the iteration and using the preconditioned conjugate gradient method to solve the equations, the stability and convergence of the inversion results can be enhanced. The results of theoretical models and actual data demonstrate that the method is effective for pre-drilling prediction using VSP data.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.300102268212)Postdoctoral Science Foundation(2013M540756,2014T70925)and the Shaanxi Natural Science Foundation(2014JQ2-4019).
文摘The goals of this study were to examine factors influencing Q inversion and to provide references for practical application.Three different methods for inverting Q values with VSP data were explored,including centroid frequency shift(CFS),spectral ratio(SR),and amplitude attenuation(AA).Comparison between the CFS and the other two methods was conducted on frequency band widths and low attenuation,wavefield components,interface interference,and thin layers.Results from several sets of VSP modeling data indicated that the CFS method is more stable and accurate for dealing with thin and high Q layers.Frequency band width,especially the presence of high frequencies,influences the inversion effect of all three methods.The wider the band,the better the results.Q inversion from downgoing wavefield was very similar to that of the upgoing wavefield.The CFS method had fewer outliers or skip values from the full wavefield than the other two methods.Moreover,the applications to Q inversion for the set of field VSP data demonstrated that the Q curves from the CFS method coincided with the geological interpretations better than the Q curves of the other methods.Meanwhile,inverse Q filtering shifted the frequency component from 25 Hz to 35 Hz.The results demonstrated that the Q curve is more sensitive to geological horizons than velocity.
