The imaging of offset VSP data in local phase space can improve the image of the subsurface structure near the well.In this paper,we present a migration scheme for imaging VSP data in a local phase space,which uses th...The imaging of offset VSP data in local phase space can improve the image of the subsurface structure near the well.In this paper,we present a migration scheme for imaging VSP data in a local phase space,which uses the Gabor-Daubechies tight framebased extrapolator（G-D extrapolator） and its high-frequency asymptotic expansion to extrapolate wavefields and also delineates an improved correlation imaging condition in the local angle domain.The results for migrating synthetic and real VSP data demonstrate that the application of the high-frequency G-D extrapolator asymptotic expansion can effectively decrease computational complexity.The local angle domain correlation imaging condition can be used to weaken migration artifacts without increasing computation.展开更多
Viscoelastic parameters are becoming more important and their inversion algorithms are studied by many researchers. Genetic algorithms are random, self-adaptive, robust, and heuristic with global search and convergenc...Viscoelastic parameters are becoming more important and their inversion algorithms are studied by many researchers. Genetic algorithms are random, self-adaptive, robust, and heuristic with global search and convergence abilities. Based on the direct VSP wave equation, a genetic algorithm （GA） is introduced to determine the viscoelastic parameters. First, the direct wave equation in frequency is expressed as a function of complex velocity and then the complex velocities estimated by GA inversion. Since the phase velocity and Q-factor both are functions of complex velocity, their values can be computed easily. However, there are so many complex velocities that it is difficult to invert them directly. They can be rewritten as a function of Co and C∞ to reduce the number of parameters during the inversion process. Finally, a theoretical model experiment proves that our algorithm is exact and effective.展开更多
In this paper,we present a method of wavelet estimation by matching well-log, VSP,and surface-seismic data.It＇s based on a statistical model in which both input and output are contaminated with additive random noise....In this paper,we present a method of wavelet estimation by matching well-log, VSP,and surface-seismic data.It＇s based on a statistical model in which both input and output are contaminated with additive random noise.A coherency matching technique is used to estimate the wavelet.Measurements of goodness-of-fit and accuracy provide tools for quality control.A practical example suggests that our method is robust and stable.The matching and estimation of the wavelet is reliable within the seismic bandwidth.This method needs no assumption on the wavelet amplitude and phase and the main advantage of the method is its ability to determine phase.展开更多
基金supported by the National Hi-Tech Research and Development Program of China (Grant No.2006AA09A102-11)the National Natural Science Fund of China (Grant No.40730424 and 40674064)
文摘The imaging of offset VSP data in local phase space can improve the image of the subsurface structure near the well.In this paper,we present a migration scheme for imaging VSP data in a local phase space,which uses the Gabor-Daubechies tight framebased extrapolator（G-D extrapolator） and its high-frequency asymptotic expansion to extrapolate wavefields and also delineates an improved correlation imaging condition in the local angle domain.The results for migrating synthetic and real VSP data demonstrate that the application of the high-frequency G-D extrapolator asymptotic expansion can effectively decrease computational complexity.The local angle domain correlation imaging condition can be used to weaken migration artifacts without increasing computation.
文摘Viscoelastic parameters are becoming more important and their inversion algorithms are studied by many researchers. Genetic algorithms are random, self-adaptive, robust, and heuristic with global search and convergence abilities. Based on the direct VSP wave equation, a genetic algorithm （GA） is introduced to determine the viscoelastic parameters. First, the direct wave equation in frequency is expressed as a function of complex velocity and then the complex velocities estimated by GA inversion. Since the phase velocity and Q-factor both are functions of complex velocity, their values can be computed easily. However, there are so many complex velocities that it is difficult to invert them directly. They can be rewritten as a function of Co and C∞ to reduce the number of parameters during the inversion process. Finally, a theoretical model experiment proves that our algorithm is exact and effective.
基金the Natural Science Foundation of China(Grant Nos.40974066 and 40821062)by the National Basic Research Program of China(Grant No.2007CB209602).
文摘In this paper,we present a method of wavelet estimation by matching well-log, VSP,and surface-seismic data.It＇s based on a statistical model in which both input and output are contaminated with additive random noise.A coherency matching technique is used to estimate the wavelet.Measurements of goodness-of-fit and accuracy provide tools for quality control.A practical example suggests that our method is robust and stable.The matching and estimation of the wavelet is reliable within the seismic bandwidth.This method needs no assumption on the wavelet amplitude and phase and the main advantage of the method is its ability to determine phase.
