Velocity ratio estimation using AVA attributes in VTI media

Amplitude variation with angle (AVA) analysis is one of the fundamental tools for hydrocarbon detection and reservoir characterization. The background trend as a function of intercept against gradient for various 〈Vp〉/〈Vs〉 ratios are well defined assuming isotropic media only. However, how the aniso...

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Bibliographic Details
Main Author: Zahid, Arslan
Other Authors: Duffaut, Kenneth
Format: Master Thesis
Language:English
Published: NTNU 2017
Subjects:
Online Access:http://hdl.handle.net/11250/2450813
Description
Summary:Amplitude variation with angle (AVA) analysis is one of the fundamental tools for hydrocarbon detection and reservoir characterization. The background trend as a function of intercept against gradient for various 〈Vp〉/〈Vs〉 ratios are well defined assuming isotropic media only. However, how the anisotropy changes this background trend is not being investigated. Therefore, this study shows the effects induced by anisotropy assuming VTI symmetry on background trends, reflectivity by using the weak contrast two term approximation. Moreover, analytical expressions for the estimation of average Vp and Vp/Vs ratios from AVA attributes (A and B) are derived and then modelled using well and seismic data from Norwegian Sea for both the isotropic and VTI media respectively. To accomplish this work, well log data, synthetic seismic CMP gathers and real seismic data were used to calculate the intercept-gradient ratios which were then implemented to generate the plots, background trends, modelling of average Vp and Vp/Vs ratios using the derived explicit equations. The modelled results obtained from the log data, synthetic seismic CMP gathers and real seismic data for the estimation of average Vp and Vp/Vs ratios are quite adequate, good. Some of the major problems encountered in this modelling was the instability caused by very low values of intercept-gradient ratios, resulting in very high values of estimated average Vp and Vp/Vs ratios, approaching infinity in magnitude. This complication was solved by applying the smoothing function. However, some of the original well data would get removed during the process of attaining the perfect modelling outcome, thereby, suggesting the need to find the optimal parameters of smoothing filter function. Another difficulty came across when modelling of estimated data values was the frequency bandwidth problem which was investigated as well. Likewise smoothing, this also requires the need to find the optimal frequency bandpass filter.