MIGRATION VELOCITY ANALYSIS USING A GENETIC ALGORITHM

Migration velocity analysis, a method for determining long wavelength velocity structure, is a critical step in prestack imaging. Solution o f this inverse problem is made difficult by a multimodal objective fun ction; a parameter space often vast in extent; and an evaluation proce dure for candidate solutions, involving the calculation of depth-migra ted image gathers, that can be prohibitively expensive. Recognizing th e global nature of the problem, we employ a genetic algorithm (GA) in the search for the optimum velocity model. In order to describe a mode l efficiently, regions of smooth variation are identified and sparsely parametrized. Region boundaries are obtained via map migration of eve nts picked on the zero-offset time section. Within a region, which may contain several reflectors, separate components describe long and sho rt wavelength variations, eliminating from the parameter space, models with large velocity fluctuations. Vital to the success of the method is rapid model evaluation, achieved by generating image gathers only i n the neighbourhood of specific reflectors. Probability of a model, wh ich we seek to maximize, is derived from the flatness of imaged events . Except for an initial interpretation of the zero-offset time section , our method is automatic in that it requires no picking of residual m oveout on migrated gathers. Using an example data set from the North S ea, we show that it is feasible to solve for all velocity parameters i n the model simultaneously: the method is global in this respect also.