Wavelet analysis for spectral inversion of seismic reflection data

Abstract

In the current work we present a seismic inversion alternative based on the spectral inversion method developed by Puyear and Castagna (2008). We incorporate the wavelet analysis to synthesize singularities of interest and obtain a detailed analysis of seismic windows. The methodology is a suitable alternative to constrained seismic inversion for determination of the reflection coefficients as functions of frequency. Moreover, the forward problem of seismic data as a function of frequency is non-linear; therefore, in order to solve the inverse problem, global optimization techniques are applied: Iterative Solution of Generalized Inversion, Genetic Algorithms and Particle Swarm Optimization. The most reliable results were obtained based on the fact that the wavelet synthesis facilitates getting the first approximation of the events retaining the characteristic amplitude and establishing the initial domain model for the optimization algorithms being only slightly slower than the deterministic deconvolution technique. We show the results of the developed methodology on synthetic and real seismic reflection data.