This study quantifies the impact of mesoscale geological heterogeneity on CO2 storage behavior, using the Pano flood-tidal delta as a case study. A hierarchical workflow was employed, progressing m simple to complex static modeling (L1 to L4) based on outcrop interpretation, followed by flow diagnostics analysis. The results reveal a non-linear relationship between model complexity and system behavior. The mesoscale architecture (L2) primarily controls early CO2 breakthrough risk, whereas the sub-lobe scale heterogeneity (L3) is crucial for reliably predicting long-term storage performance and sweep efficiency.
A key insight from this work is that the level of model complexity systematically biases the simulated flow narrative. Consequently, there is no single ”correct” model; instead, the choice of complexity inherently pre-selects which aspects of storage behavior (e.g., early risk vs. long-term efficiency) will be most accurately represented. This provides a decision-making framework for CO2 storage projects, demonstrating that distinct optimal levels of model complexity exist for specific engineering objectives, such as using L2 for risk identification and L3 for performance prediction—thereby guiding more effective and intentional model deployment.