Data-Driven Rock Physics Analysis of North Sea Tertiary Reservoir Sands

We have demonstrated an approach for data-driven rock physics analysis, where we first do facies classification using elastic well log data from several wells, followed by facies-constrained regression analysis to establish local rock physics relations for prediction of Vp and Vs from geological input parameters. We have applied this approach to a multi-well log data set (40 wells) from a given area in the North Sea, focusing on Tertiary age reservoir sands. We show how we can derive very robust local empirical rock physics relations for prediction of P-wave and S-wave velocities as well as densities, for given combinations of porosity and clay volume. These results are more accurate than universal rock-physics models, even when the latter are locally calibrated. Using elastic facies with geological characteristics (cemented versus unconsolidated; normally compacted versus injectites; homogenous versus heterogeneous) helps to improve the predictability of the regression models. The local rock physics relations that we obtain can furthermore be used to create training-data for AVO classification in future projects.