A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical po...A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical porosity value and we can generally take only an empirical critical porosity value which often causes errors. In this paper, we propose a method to obtain the rock critical porosity value by inverting P-wave velocity and applying it to predict S-wave velocity. The applications of experiment and log data both show that the critical porosity inversion method can reduce the uncertainty resulting from using an empirical value in the past and provide the accurate critical porosity value for predicting S-wave velocity which significantly improves the prediction accuracy.展开更多
First arrival travel time tomography has achieved wide application. However, tomographic resolution is insufficient because geometry constraints cause rays to be unevenly distributed in the velocity model. The variabl...First arrival travel time tomography has achieved wide application. However, tomographic resolution is insufficient because geometry constraints cause rays to be unevenly distributed in the velocity model. The variable damping constraint method adopts uneven priori information to match uneven data distribution which can lessen the correlation between velocity correction values and ray coverage density. In this paper, we combine the variable damping constraint with a smoothness constraint which is added into the regularization equations in velocity inversion to avoid instability caused by only using the variable damping constraint method. The alpha-trimmed-mean filter is used to smooth and denoise intermediate results in the velocity inversion process. We use the LSQR algorithm to enhance the convergence rate and suppress error propagation in solving linear equations. In this paper, we apply the proposed tomographic method to perform velocity inversion using VSP data. The application in recovery test of the checkerboard model and velocity inversion of real VSP data show that the variable damping constraint method can improve tomographic quality because it can solve the effects of uneven ray coverage. In addition, the examples show that the tomographic result near geophones is much more reliable than other areas in the velocity model.展开更多
An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear glob...An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.展开更多
基金sponsored by Important National Science and Technology Specifi c Projects of China (No.2011ZX05001)
文摘A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical porosity value and we can generally take only an empirical critical porosity value which often causes errors. In this paper, we propose a method to obtain the rock critical porosity value by inverting P-wave velocity and applying it to predict S-wave velocity. The applications of experiment and log data both show that the critical porosity inversion method can reduce the uncertainty resulting from using an empirical value in the past and provide the accurate critical porosity value for predicting S-wave velocity which significantly improves the prediction accuracy.
基金supported by the China Important National Science and Technology Specific Projects (No2011ZX05024-001-02)
文摘First arrival travel time tomography has achieved wide application. However, tomographic resolution is insufficient because geometry constraints cause rays to be unevenly distributed in the velocity model. The variable damping constraint method adopts uneven priori information to match uneven data distribution which can lessen the correlation between velocity correction values and ray coverage density. In this paper, we combine the variable damping constraint with a smoothness constraint which is added into the regularization equations in velocity inversion to avoid instability caused by only using the variable damping constraint method. The alpha-trimmed-mean filter is used to smooth and denoise intermediate results in the velocity inversion process. We use the LSQR algorithm to enhance the convergence rate and suppress error propagation in solving linear equations. In this paper, we apply the proposed tomographic method to perform velocity inversion using VSP data. The application in recovery test of the checkerboard model and velocity inversion of real VSP data show that the variable damping constraint method can improve tomographic quality because it can solve the effects of uneven ray coverage. In addition, the examples show that the tomographic result near geophones is much more reliable than other areas in the velocity model.
基金This work is supported by National Natural Science Foundation of China （Grant No.40839905）.
文摘An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.
