This study describes a successful multidisciplinary work flow for quantitative lithology prediction from prestack angle gathers and petrophysical well log data within the Realgrunnen Subgroup in the Goliat Field, Norwegian Barents Sea. An amplitude-versus-angle (AVA) qualitative attribute analyses was performed to assess the spatial distribution of lithology anomalies from the seismic data. A simultaneous prestack elastic inversion was also carried out for quantitative estimates of P-impedance and Vp/Vs ratios which were subsequently analysed using 3D cross plots. Probability distribution functions (PDFs), and a priori lithology class proportions extracted from the well log training data are then applied to the inverted seismic volume.

AVA qualitative analyses showed a class-IV top reservoir response, and lithology anomalies interpreted from the scaled S-wave reflectivity attribute map revealed a qualitative spatial distribution of the reservoir sands. The confusion matrix from the best training dataset shows the largest misclassification between shaly sands and shales. PDFs from a rule based ternary lithology classification provided the best resolution for the clean sands. A good match is obtained between horizon attributes generated from angle gathers and that obtained from the clean sand and shaly sand probability maps combined.


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