Abstract

Seismic reservoir characterization in geologic settings with coals, anhydrites and gas clouds is known to be challenging due to transmission effects and non-primary energy noise introduced by these strong velocity contrasts. These full wavefield effects mask the amplitude response of underlying reservoirs is well known and understood to be difficult to overcome in AVO inversion workflows. In this paper, we compare a standard AVO inversion workflow, which relies on standard convolutional modelling, to a new workflow that uses 1D tau-p domain wave equation as the forward model in an effort not only to more accurately model the input seismic data, but to use the short period multiples and mode conversions to improve AVO inversion results. In the examples shown, we observe that the inclusion of mode conversions in the forward model provides a better match to the observed seismic at the reservoir level. The updated AVO inversion algorithm, which includes mode conversions and multiples, improves the predictability of the Vp/Vs ratio.