A new implementation of the beam migration by using a model-driven variable grid strategy

Beam migration offers higher imaging accuracy, better flexibility, stability and adaptability than conventional ray migration, while the variable grid method achieves lower storage and higher efficiency under the same accuracy by means of different grid generation of the velocity model. However, the efficiency and accuracy of Gaussian beam migration are strongly affected by the algorithm used for Gaussian beam summation whose key step is to find the underground point at which the local beam contributes relevantly to the reconstruction of the Green's function. Conventionally, one uses Hale's recursive search method that firstly searches on a global coarse grid and then interpolated to a local fine one. Practical experience shows that this method can greatly improve the efficiency of the beam scanning, but causes some wavy discontinuities and imaging artifacts as well. To solve this problem, we present a new method called "model-driven variable grid strategy". In this strategy, a key step is to establish a relationship between the vertical gradient of the velocity model and the local grid constants through local velocity gradient with respect to the global average velocity. Numerical tests on synthetic and field data show that the new method has a minimal need on computer resources and can largely improve the accuracy and efficiency of the beam migration in regions with complex geological structures.