The aim of the study was to predict lithology and fluid
content away from the well bore, and in particular to identify
gas sands. The process made use of all available data, not
just well and seismic data in isolation. Geological insight
contributed to the selection of meaningful seismic attributes
and the derivation of valid inversion products. Uncertainty
modelling was taken into account to permit risk assessment
and foster confidence in the predictions. The use of the
Bayesian framework enabled prior knowledge such as a
geological model to be incorporated into a probabilistic
prediction, which captured uncertainty and quantified risk.