Determining Characteristic Relative Permeability From Coreflooding Experiments: A Simplified Model Approach

Relative permeability measurements from drainage coreflooding experiments are effective properties that vary with injection rate when capillary heterogeneity effects are present. It is therefore important to estimate the fine-scale characteristic relative permeability (k^char _r), which is independent of flow rate and can be used for accurate reservoir simulation and numerical modeling of coreflooding. Previous methods for k^char _r estimation are based on two-phase flow simulations with fine-scale heterogeneous permeability and capillary pressure. These are computationally complex and prone to error. This work presents a reduced method, based on a simplified model, requiring only solutions of steady state single-phase flow equations. The simplified model is used to study a number of synthetic 2-D permeability realizations and 3-D core models constructed based on experimental data from previous literature. The k^char _r estimation method is tested on these examples and shown to be generally accurate. Cases where estimation error is significant are characterized by low injection rates, large nonwetting phase fractional flow, strong capillary heterogeneity, and small capillary number (ratio between core average pressure drop and capillary pressure drop). The estimation error is believed to be related to errors in the full-model (two-phase flow) simulations; that is, we find that for low injection rates, our simulator presents significantly different results compared to a commercial simulator. This could explain the source of mismatch between full and simplified methods and calls for further investigation of inaccuracy in numerical simulations at low flow rates, which could have implications for coreflood modeling and low rate reservoir simulation.