HYBRID OPTIMIZATION OF STATIC ESTIMATION IN COMPLEX TOPOGRAPHY
复杂地形条件下静校正的综合寻优

For the areas of complex topography, especially mountain area, static is a non-linear hybrid optimization problem with the presence of multi-parameters and multi-extremes. A hybrid optimization inversion method is developed to calculate large static by integrating stack power maximization, stimulated annealing and genetic algorithms. This method has a series of advantages, such as high-speed regional convergence and efficient global searching ability. A special smooth filtering operator is used to eliminate the pseudo-static null space phenomenon. Checking with synthetic and real seismic data shows that this method is adaptable and effective to process seismic data acquired in the areas with complex tomography.