Modeling Viscous Oil and Tar Mat Formation from Nanoscale to Macroscale

Viscous oil and tar mats often occur at and near the oil-water contact (OWC) and can result from multiple charges of incompatible fluids with regard to asphaltene stability. The most easily measured oilfield case is gas charge into oil, where the increase of solution gas near the gas-oil contact (GOC) causes local instability of asphaltenes which can then lead to viscous oil and tar mats at the OWC. However, the detailed mechanisms that occur in geologic time to transport destabilized asphaltenes over large distances from the GOC to the OWC has yet to be fully resolved. Asphaltene destabilization towards the top of the reservoir, transport and accumulation at the base of the reservoir can be treated within a conceptual multistep process: instability driven by diffusion of light ends into the oil at the GOC, Stokes falling and diffusion of asphaltene nanocolloidal particles to the base of the interval, convective transport to the base of the reservoir, and finally, local asphaltene equilibration at the base of the reservoir. This conceptual model lays the foundation and provides the framework for forward modeling the formation of viscous oil and tar mats at the OWC. Here we introduce a simple, one-dimension composite model that accounts for all key physics and chemistry aspects of asphaltene instability, transport outcomes and bulk phase transition. This model can be used to predict different reservoir realizations given specific charge fluids, timing of charge, and reservoir attributes. This model employs the asphaltene thermodynamic equation, the Flory-Huggins-Zuo equation of state, and its reliance on the asphaltene nanostructures in the Yen-Mullins model and is shown to be applicable from nanoscale to macroscale. In a broader context, these reservoir processes fall within the new technical discipline ‘reservoir fluid geodynamics’. The target applications for this modeling include identification of possible key reservoir performance drivers through generation of different possible reservoir realizations and as a job planner for data acquisition and analysis to differentiate among reservoir realizations for optimization of field development planning. This approach is a template for forward modeling a broad array of fluid and rock complexities through a comprehensive deposition, trap filling and geodynamics perspective.