The rule-based modeling method applies stratigraphic rules that simulate the fundamental geological processes to generate numerical subsurface models. Even though rule-based models rely upon a few simple and intuitive rules, they can create complicated and realistic reservoir heterogeneity, continuity, and spatial organization. The application of this modeling approach has now been applied to a variety of depositional settings, such as the deepwater turbidites, efficiently capturing the salient geological spatial features of compensational stacked lobes. Questions remain as to how the integration of geological rules and related parameters affect the forecasting of fluid flow, including oil production. A large experiment was conducted using a rule-based model for a deepwater lobe system controlled by three key geological parameters: (1) the vertical and lateral stacking of geobodies, described as a compensation index; (2) lobe geometry/size; and (3) permeability heterogeneity. Regression analysis and computational physics–based fluid flow simulation are applied to examine reservoir production sensitivity to these three geological input parameters. Over the early production stage, the permeability heterogeneity within depositional elements is the most influential reservoir parameter. However, over time, lobe geometry and compensation index have a more significant impact on production. This result suggests that the importance of geological features to the flow behavior changes over time as longer-term production is influenced by a larger rock volume and compounding heterogeneity. Moreover, understanding the impact of compensational stacking and deepwater lobe geometry is essential for performance forecasting, uncertainty analysis, and history matching. The importance of these key geologic parameters further supports the necessity of outcrop characterization, high-resolution seismic interpretation and flume experiments, and the use of reservoir models, such as stratigraphic rule-based models that reproduce these critical stratigraphic features.