We propose a workflow to optimize the configuration of multiple-interacting-continua (MINC) models and overcome the limitations of the classical dual-porosity (DP) model when simulating chemical-component-transport processes during two-phase flow. Our new approach captures the evolution of the saturation and concentration fronts inside the matrix, which is key to design more effective chemical enhanced-oil-recovery (CEOR) projects in naturally fractured reservoirs. Our workflow is intuitive and derived from the simple concept that fine-scale single-porosity (SP) models capture fracture/matrix interaction accurately; it can hence be easily applied in any reservoir simulator with MINC capabilities. Results from the fine-scale SP model are translated into an equivalent MINC model that yields more accurate results compared with a classical DP model for oil recovery by spontaneous imbibition; for example, in a water-wet (WW) case, the root-mean-square error (RMSE) improves from 0.123 to 0.034. In general, improved simulation results can be obtained when selecting five or fewer shells in the MINC model. However, the actual number of shells is case specific. The largest improvement in accuracy is observed for cases where the matrix permeability is low and fracture/matrix transfer remains in a transient state for a prolonged time. The novelty of our approach is the simplicity of defining shells for a MINC model such that the chemical-component-transport process in naturally fractured reservoirs can be predicted more accurately, especially in cases where the matrix has low permeability. Hence, the improved MINC model is particularly suitable to model chemical-component transport, key to many CEOR processes, in (tight) fractured carbonates.
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Geotechnical Engineering and Engineering Geology