Research Of Residual Static Correction Using Simulated Annealing And Genetic Algorithm

In complex surface areas, residual static correction is a pivotal and basic work, which is essential to seismic data acquisition and processing. When the S/N ratio is low or the residual statics are larger than half of the wavelet period, residual statics must be resolved by optimization methods to avoid the"cycle-skips"phenomenon.The paper firstly formulates classifications of static correction methods and the nonlinear characteristics of residual static correction. Then the basic principles and characteristics of the simulated annealing and genetic algorithm are introduced. Secondly, the geometry relations of 2D survey is studied and the objective functions of the optimization algorithm are designed. Subsequently, after analyzing the schemes of parameter selections, the simulated annealing and hybrid genetic algorithm are applied to theoretical models and practical seismic data, which makes both resolutions of the stacked profiles and continuity of the layers enhanced. Finally, a little sentiment about static correction and optimization algorithm is summarized during this period.In this paper, super-trace crosscorrelation is used as objective function to avoid"cycle-skips"and reduce computations. Secondly, the"heat bath"algorithm is used to calculate statics. Thirdly, combined with simulated annealing algorithm, the fitness function is scaled to implement hybrid genetic algorithm for static correction. All of this three points are the key work of this paper.