ANALYSIS OF ONE-DIMENSIONAL SEISMIC WAVE-FORM INVERSION BY REGULARIZED GLOBAL APPROXIMATION

Citation
G. Ryzhikov et al., ANALYSIS OF ONE-DIMENSIONAL SEISMIC WAVE-FORM INVERSION BY REGULARIZED GLOBAL APPROXIMATION, Journal of seismic exploration, 5(4), 1996, pp. 349-362
Citations number
14
Categorie Soggetti
Geochemitry & Geophysics
ISSN journal
09630651
Volume
5
Issue
4
Year of publication
1996
Pages
349 - 362
Database
ISI
SICI code
0963-0651(1996)5:4<349:AOOSWI>2.0.ZU;2-R
Abstract
Direct analysis of normal incidence seismogram inversion with respect to a velocity profile is now available due to application of a new glo bal optimization algorithm. The latter is based on regularized global approximation of an objective function which is not supposed to re dif ferentiable. The new technique allows one to see clearly a nonuniquene ss of the inversion problem, no matter how high the quality of the inp ut data may be. It is induced by a few factors: a source wavelet is a function of a finite frequency band, an effective wave length of the s ounding signal is increasing jointly with the velocity, and the power of a media response is decreasing with respect to the depth. The nonun iqueness means that no inversion/processing is capable of solving the problem if it does not take into account a priori information about th e recovered velocity profile. It is shown how an a priori assumption a bout a trend of the profile can essentially reduce the nonuniqueness o f the problem. The corresponding regularization has the form of a soft constraint on the misfit function and leads to an unbiased estimation of the velocity profile when the latter is a monotonous function with respect to the depth. On the other hand, the regularization suggested allows of reconstructing nonmonotonous functions as well, which leads to a biased estimation of the velocity profile as any conventional re gularized inversion also does. Examples of computer experiments are gi ven that yield an opportunity of reconstructing the images of nonregul arized and regularized objective functions as well as determining the accuracy of corresponding solutions of the inverse problem.