LAYER THICKNESS DETERMINATION FORTHIN BEDS

Abstract

Stratigraph Ic interpretation has become increasingly important in today's hydrocarbon exploration due to reduction in availability of easy oil. Characterization of thin beds for thickness and impedance is thus needed. These thin pay zones across the world consists of considerable amount of reserves. The aim of this dissertation is to resolve thin beds beyond tuning thickness using Spectral Inversion method. It also encompasses determination of reflectivities (Top and bottom) of the bed. The results obtained have also been compared with that of non-spectral method. The spectral inversion method uses spectral decomposition followed by global minimization ofan objective function. Mathematically speaking, the error between data-dependent function and a model-parameter-dependent function is minimized over the model parameter space, to obtain the optimum values of model parameters. The inverted model thus obtained is identical to the initial wedge model for 0% Signal to Noise ratio (SNR); and has well resolved thickness up-to 40% of tuning thickness for noise levels less than 10% SNR. The spectral method works especially well for the predominantly odd wedge models, where the amplitude of traces is very low beyond the tuning thickness due to mutual canceling out of reflection amplitudes.