Evaluation of the Sensitivity of Seismic Inversion Algorithms to Different Statistically Estimated Wavelets

Abstract

Seismic wavelet estimation is an important step in processing and analysis of seismic data. Inversion methods as Narrow-Band and theConstrained Sparse-Spike ones require information about it so that the inversion solution, once it is not a unique problem, may be restricted by comparing the real seismic trace with the synthetic generated by convolution of the estimated reflectivity and wavelet. Besides helping in seismic inversion, a good estimate of the wavelet enables an inverse filter with less uncertainty to be computed in the deconvolution step and while tying well logs, a better correlation between the seismic trace and well log can be achieved. Depending on the use or not of well log information, the methods of wavelet estimation can be divided into two classes: statistical and deterministic. This work aimed to test the sensitivity of acoustic post-stack seismic inversion algorithms to wavelets statistically estimated by two distinct methods.