Sequence, stratigraphic-based analysis of reservoir connectivity: influence of depositional architecture - a case study from a marginal marine depositional setting

This case study of the Sunrise and Troubadour fields (offshore northwest Australia) concentrates on the impact of primary depositional architecture on reservoir connectivity via a sequence stratigraphic-based, 3D reservoir modelling approach. The marginal marine reservoir is composed of fluvial-dominated and wave-dominated depositional environments. The succession is divided into six sequences and 12 systems tracts. Each systems tract is subdivided into parasequences which form the basic building blocks of the 3D model. The connectivity of sandbodies within each parasequence, systems tract and sequence were calculated when the models were palinspastically restored to a depositional datum. The findings indicate that depositional connectivity trends within a sequence stratigraphic framework Are predictable. Connectivity trends can be related directly to depositional and stratigraphic trends and to position in the sequence stratigraphic hierarchy. Therefore, with a good understanding of depositional settings and high resolution sequence stratigraphic subdivision of strata, predictions of depositional connectivity trends at all stratigraphic hierarchical levels can be made. All connectivity trends at sequence and systems tract stratigraphic hierarchical levels remained the same when the area of the model was reduced by a factor of four and the volume of the model was reduced by truncation below the gas-water contact. Hence, the relationships between the stratigraphic trends and the connectivity trends for the thicker stratigraphic units can be said to be scale invariant. Three-dimensional reservoir models currently provide the best means of quantitatively assessing and predicting reservoir connectivity. However, in low fault density settings, initial screening of reservoir connectivity can be made using connectivity indicators calculated from simple parameters derived from well data such as 'Thickness divided by Sand/Shale ratio'.