--> Lacustrine Carbonate Platform Development —A Multi-Scale Approach to Build Predictive Models

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Lacustrine Carbonate Platform Development —A Multi-Scale Approach to Build Predictive Models


Lower Cretaceous carbonate reservoirs in the Pre-Salt of Brazil will be a significant part of future global hydrocarbon exploration and exploitation. With this in mind, it is important to have conceptual models for carbonate deposition that are grounded in subsurface datasets. A variety of concepts have been presented on the Pre-Salt reservoir depositional system. Interpretations range from shallow evaporitic lakes with chemically driven sedimentation, to small sub-regional semi-connected lakes, and to lacustrine platforms that develop on highs as part of a major lake setting with both chemical and microbially mediated depositional processes. Wide variations in interpretation arise from low resolution seismic datasets and the lack of proper outcrop analogs that match the scale and magnitude of the Pre-Salt subsurface. We have focused our efforts to understand the depositional controls on platform development and architecture across the Santos Basin on seismic-based observations calibrated to well-logs and core observations. We place an emphasis on leveraging seismic data as our key dataset given its spatial coverage, but recognize its limited resolution. The use of multi-volume attribute analysis to develop seismic scale environments of deposition maps is a key part of our approach to characterize exploration opportunities. We apply this approach to a 200 km2 lacustrine carbonate platform developed on the flank of the large Sugarloaf volcanic high. Faulting of the large basalt complex created the antecedent topography necessary for the sedimentation of shallow-water lake carbonates. The platform initially developed in the Lower Aptian as a ramp system that transitioned into a raised-rim platform with lake water depths estimated to be up to 350 meters. Core observations highlight an abundance of coarse cross-bedded grain-dominated fabrics that are consistent with the interpretation of deposition on a high-energy platform top behind a shelf edge mound. Our methodology explains the variability in reservoir quality observed at the wellbore, and can be applied to predict reservoir properties across the platform away from well control. This multi-scale approach builds the foundation for our predictive capabilities in the Pre-Salt and provides an integration tool for key datasets that increase our understanding of carbonate platform architecture globally.