Angle-domain common-image gathers（ADCIGs） are the basic data in migration velocity analysis（MVA） and amplitude variation with angle（AVA） analysis. We propose a common-angle gather-generating scheme using Kirchho...Angle-domain common-image gathers（ADCIGs） are the basic data in migration velocity analysis（MVA） and amplitude variation with angle（AVA） analysis. We propose a common-angle gather-generating scheme using Kirchhoff PSDM based on the traveltime gradient field. The scheme includes three major operations：（1） to calculate the traveltime field of the source and the receiver based on the dynamic programming approach;（2） to obtain the refl ection angle according to the traveltime gradient field in the image space; and（3） to generate the ADCIGs during the migration process. Because of the computation approach, the method for generating ADCIGs is superior to conventional ray-based methods. We use the proposed ADCIGs generation method in 3D large-scale seismic data. The key points of the method are the following.（1） We use common-shot datasets for migration,（2） we load traveltimes based on the shot aperture, and（3） we use the MPI and Open Mp memory sharing to decrease the amount of input and output（I/O）. Numerical examples using synthetic data suggest that the ADCIGs improve the quality of the velocity and the effectiveness of the 3D angle-gather generation scheme.展开更多
To support amplitude variation with offset （AVO） analysis in complex structure areas, we introduce an amplitude-preserving plane-wave prestack time migration approach based on the double-square-root wave equation in...To support amplitude variation with offset （AVO） analysis in complex structure areas, we introduce an amplitude-preserving plane-wave prestack time migration approach based on the double-square-root wave equation in media with little lateral velocity variation. In its implementation, a data mapping algorithm is used to obtain offset-plane-wave data sets from the common-midpoint gathers followed by a non-recursive phase-shift solution with amplitude correction to generate common-image gathers in offset-ray-parameter domain and a structural image. Theoretical model tests and a real data example show that our prestack time migration approach is helpful for AVO analysis in complex geological environments.展开更多
Prestack depth migration of multicomponent seismic data improves the imaging accuracy of subsurface complex geological structures. An accurate velocity field is critical to accurate imaging. Gaussian beam migration wa...Prestack depth migration of multicomponent seismic data improves the imaging accuracy of subsurface complex geological structures. An accurate velocity field is critical to accurate imaging. Gaussian beam migration was used to perform multicomponent migration velocity analysis of PP- and PS-waves. First, PP- and PS-wave Gaussian beam prestack depth migration algorithms that operate on common-offset gathers are presented to extract offsetdomain common-image gathers of PP- and PS-waves. Second, based on the residual moveout equation, the migration velocity fields of P- and S-waves are updated. Depth matching is used to ensure that the depth of the target layers in the PP- and PS-wave migration profiles are consistent, and high-precision P- and S-wave velocities are obtained. Finally, synthetic and field seismic data suggest that the method can be used effectively in multiwave migration velocity analysis.展开更多
Least squares migration can eliminate the artifacts introduced by the direct imaging of irregular seismic data but is computationally costly and of slow convergence. In order to suppress the migration noise, we propos...Least squares migration can eliminate the artifacts introduced by the direct imaging of irregular seismic data but is computationally costly and of slow convergence. In order to suppress the migration noise, we propose the preconditioned prestack plane-wave least squares reverse time migration （PLSRTM） method with singular spectrum constraint. Singular spectrum analysis （SSA） is used in the preconditioning of the take-off angle-domain common-image gathers （TADCIGs）. In addition, we adopt randomized singular value decomposition （RSVD） to calculate the singular values. RSVD reduces the computational cost of SSA by replacing the singular value decomposition （SVD） of one large matrix with the SVD of two small matrices. We incorporate a regularization term into the preconditioned PLSRTM method that penalizes misfits between the migration images from the plane waves with adjacent angles to reduce the migration noise because the stacking of the migration results cannot effectively suppress the migration noise when the migration velocity contains errors. The regularization imposes smoothness constraints on the TADCIGs that favor differential semblance optimization constraints. Numerical analysis of synthetic data using the Marmousi model suggests that the proposed method can efficiently suppress the artifacts introduced by plane-wave gathers or irregular seismic data and improve the imaging quality of PLSRTM. Furthermore, it produces better images with less noise and more continuous structures even for inaccurate migration velocities.展开更多
基金funded by the National Basic Research Program of China(973 Program)(No.2011 CB201002)the National Natural Science Foundation of China(No.41374117)the great and special projects(No.2011ZX05003-003,2011ZX05005-005-008 HZ,and 2011ZX05006-002)
文摘Angle-domain common-image gathers（ADCIGs） are the basic data in migration velocity analysis（MVA） and amplitude variation with angle（AVA） analysis. We propose a common-angle gather-generating scheme using Kirchhoff PSDM based on the traveltime gradient field. The scheme includes three major operations：（1） to calculate the traveltime field of the source and the receiver based on the dynamic programming approach;（2） to obtain the refl ection angle according to the traveltime gradient field in the image space; and（3） to generate the ADCIGs during the migration process. Because of the computation approach, the method for generating ADCIGs is superior to conventional ray-based methods. We use the proposed ADCIGs generation method in 3D large-scale seismic data. The key points of the method are the following.（1） We use common-shot datasets for migration,（2） we load traveltimes based on the shot aperture, and（3） we use the MPI and Open Mp memory sharing to decrease the amount of input and output（I/O）. Numerical examples using synthetic data suggest that the ADCIGs improve the quality of the velocity and the effectiveness of the 3D angle-gather generation scheme.
文摘To support amplitude variation with offset （AVO） analysis in complex structure areas, we introduce an amplitude-preserving plane-wave prestack time migration approach based on the double-square-root wave equation in media with little lateral velocity variation. In its implementation, a data mapping algorithm is used to obtain offset-plane-wave data sets from the common-midpoint gathers followed by a non-recursive phase-shift solution with amplitude correction to generate common-image gathers in offset-ray-parameter domain and a structural image. Theoretical model tests and a real data example show that our prestack time migration approach is helpful for AVO analysis in complex geological environments.
基金supported by the National Special Fund of China(No.2011ZX05035-001-006HZ,2011ZX05008-006-22,2011ZX05049-01-02,and 2011ZX05019-003)the National Natural Science Foundation of China(No.41104084)the PetroChina Innovation Foundation(No.2011D-5006-0303)
文摘Prestack depth migration of multicomponent seismic data improves the imaging accuracy of subsurface complex geological structures. An accurate velocity field is critical to accurate imaging. Gaussian beam migration was used to perform multicomponent migration velocity analysis of PP- and PS-waves. First, PP- and PS-wave Gaussian beam prestack depth migration algorithms that operate on common-offset gathers are presented to extract offsetdomain common-image gathers of PP- and PS-waves. Second, based on the residual moveout equation, the migration velocity fields of P- and S-waves are updated. Depth matching is used to ensure that the depth of the target layers in the PP- and PS-wave migration profiles are consistent, and high-precision P- and S-wave velocities are obtained. Finally, synthetic and field seismic data suggest that the method can be used effectively in multiwave migration velocity analysis.
基金supported by the National Science and Technology Major Project(No.2016ZX05014-001-008)the National Key Basic Research Program of China(No.2014CB239006)+2 种基金the National Natural Science Foundation of China(Nos.41104069 and 41274124)the Open foundation of SINOPEC Key Laboratory of Geophysics(No.33550006-15-FW2099-0033)the Fundamental Research Funds for Central Universities(No.16CX06046A)
文摘Least squares migration can eliminate the artifacts introduced by the direct imaging of irregular seismic data but is computationally costly and of slow convergence. In order to suppress the migration noise, we propose the preconditioned prestack plane-wave least squares reverse time migration （PLSRTM） method with singular spectrum constraint. Singular spectrum analysis （SSA） is used in the preconditioning of the take-off angle-domain common-image gathers （TADCIGs）. In addition, we adopt randomized singular value decomposition （RSVD） to calculate the singular values. RSVD reduces the computational cost of SSA by replacing the singular value decomposition （SVD） of one large matrix with the SVD of two small matrices. We incorporate a regularization term into the preconditioned PLSRTM method that penalizes misfits between the migration images from the plane waves with adjacent angles to reduce the migration noise because the stacking of the migration results cannot effectively suppress the migration noise when the migration velocity contains errors. The regularization imposes smoothness constraints on the TADCIGs that favor differential semblance optimization constraints. Numerical analysis of synthetic data using the Marmousi model suggests that the proposed method can efficiently suppress the artifacts introduced by plane-wave gathers or irregular seismic data and improve the imaging quality of PLSRTM. Furthermore, it produces better images with less noise and more continuous structures even for inaccurate migration velocities.
