Using 3D Digital Modeling to Identify Reservoir Heterogeneities: A Case Study from the Rio Bonito Formation, Paraná Basin, Brazil

The storage of carbon dioxide (CO₂) in depleted hydrocarbon reservoirs and saline aquifers is regarded as a key strategy to mitigate the accumulation of greenhouse gases in the atmosphere. Evaluating a geological formation for CO₂ storage requires assessing its capacity, injectivity, and trapping mechanisms, all of which depend on its geological and petrophysical properties. Outcrops of sedimentary rocks that serve as reservoir analogues have increasingly been used to support the determination of spatial and temporal distribution parameters and reservoir heterogeneities. These outcrops provide essential geological information for understanding subsurface rock characteristics, including geometry, textural and compositional variations, and diagenetic features. Among the different reservoir types, saline aquifers are considered the most promising for geological carbon storage due to their high capacity and broad regional distribution. In this context, within the Paraná Basin, the Rio Bonito Formation stands out as a potential target for CO₂ storage because of its favorable lithological characteristics. The sandstones of this formation, deposited in a transgressive setting, encompass a wide range of depositional systems, from tide-influenced environments to wave-dominated platforms. High-resolution sedimentological, stratigraphic, and structural information obtained from outcrops plays a crucial role in refining the understanding of subsurface reservoir rocks. Detailed stratigraphic surveys are greatly enhanced by 3D outcrop modelling, which has advanced through the use of digital photogrammetry and laser-scanning techniques. When applied with unmanned aerial vehicles (UAVs), these methods enable the acquisition, processing, and integration of large datasets with high spatial accuracy. This study aimed to characterize the depositional architecture and identify macro- and mesoscale heterogeneities using a 3D digital outcrop model. Five photofacies were distinguished based on the visual tracing of photohorizons, erosional surface patterns, and image-based color and texture criteria. These photofacies supported the identification of stacking patterns and the definition of key architectural elements. The high-resolution stratigraphic elements exhibit geometries ranging from lenticular to tabular, with moderate to high lateral continuity. Laterally extensive deposits are associated with wave-dominated shoreface and barrier-lagoon systems, whereas lenticular bodies with moderate lateral traceability correspond to tidal channels and bar deposits.
Overall, the integration of detailed outcrop analysis with high-resolution 3D modelling provides a robust framework for characterizing the depositional architecture and heterogeneity of potential CO₂ storage reservoirs. The identified photofacies and their associated geometries offer valuable insights into the spatial continuity and connectivity of sedimentary bodies within the Rio Bonito Formation, reinforcing its suitability as a saline-aquifer reservoir analogue. By improving the understanding of reservoir-scale variability, this approach enhances predictions of capacity, injectivity, and trapping efficiency, thereby contributing to more reliable assessments of the formation’s potential for geological carbon storage.