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Results
Amplitude-Preserved Gaussian Beam Migration Based on Wave Field Approximation in Effective Vicinity Under Rugged Topography Condition
Yang, J.D. (China University of Petroleum) | Huang, J.P. (China University of Petroleum) | Wang, X. (China University of Petroleum) | Li, Z.C. (China University of Petroleum)
Summary Gaussian beam migration combines the ray theory with wave theory, which not only retains the advantage of Kirchhoff migration, such as flexibility, efficiency and nature adaptability for rugged topography, but also has high imaging accuracy like wave equation migration. A method of the amplitude-preserved Gaussian beam migration based on wave field approximation in effective vicinity under rugged topography condition is developed in this article. By considering the elevation, dip angle of rugged topography, we derived the forward and inverse wave extrapolation formula in terms of Gaussian beam, and then applied them to deconvolution imaging condition to obtain the formula of amplitude-preserved Gaussian beam migration in shot domain. Comparing to conventional local static correction method, our method not only applies more correction of travel time caused by rugged topography to improve the imaging quality in terms of kinematics, but also gives full consideration to the influence on the amplitude caused by rugged topography to improve the imaging quality in terms of dynamics. The trial of numerical models proved the above conclusion.
Summary We present a method based on least-squares reverse time migration with plane-wave encoding (P-LSRTM) for rugged topography. Instead of modifying the wave field before migration, we modify the plane-wave encoding function and fill constant velocity to the area above rugged topography in the model so that P-LSRTM can be directly performed from rugged surface in the way same to shot domain reverse time migration. Numerical test on SEG rugged topography model show that P-LSRTM can suppress migration artifacts in the migration image, and compensate amplitude in the middle-deep part. Without datum correction, P-LSRTM can produce a satisfying image of near-surface if we could get an accurate nearsurface velocity model. The potential drawback is that this method can only perform with fixed acquisition geometry.