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Migration velocity analysis using a genetic algorithm[Note 1. Paper presented at the 57th EAGE Conference—Geophysical Division, Glasgow, ...]
Author(s) -
Docherty Paul,
Silva Ron,
Singh Satish,
Song ZhongMin,
Wood Margaret
Publication year - 1997
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1046/j.1365-2478.1997.640298.x
Subject(s) - algorithm , offset (computer science) , computer science , inversion (geology) , residual , inverse problem , parameter space , wavelength , a priori and a posteriori , geology , mathematics , optics , geometry , physics , mathematical analysis , seismology , philosophy , epistemology , tectonics , programming language
Migration velocity analysis, a method for determining long wavelength velocity structure, is a critical step in prestack imaging. Solution of this inverse problem is made difficult by a multimodal objective function; a parameter space often vast in extent; and an evaluation procedure for candidate solutions, involving the calculation of depth‐migrated image gathers, that can be prohibitively expensive. Recognizing the global nature of the problem, we employ a genetic algorithm (GA) in the search for the optimum velocity model. In order to describe a model efficiently, regions of smooth variation are identified and sparsely parametrized. Region boundaries are obtained via map migration of events picked on the zero‐offset time section. Within a region, which may contain several reflectors, separate components describe long and short 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 in the neighbourhood of specific reflectors. Probability of a model, which 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 moveout on migrated gathers. Using an example data set from the North Sea, we show that it is feasible to solve for all velocity parameters in the model simultaneously: the method is global in this respect also.