A Versatile Representation of Upscaled Relative Permeability for Field Applications (SPE 154487)

A suitable approach to achieve a fit-for-purpose model for field application is upscaling of reservoir properties. However, upscaling of saturation functions like relative permeability is still a source of debate and is frequently omitted due to its inconvenient complexity. Upscaling of these functions, whether by steady-state methods or other techniques, typically generates a complex myriad of relative permeability curves that is challenging to handle pragmatically. This study investigates whether a three-parameter correlation of relative permeability is able to represent the saturation function for fine grid simulation models with the most common heterogeneities, coarse grid simulation models with upscaled properties in addition to verify two-phase core-flow experiments. To demonstrate the applicability of two flexible three-parameter correlations at the field simulation scale, we have utilized three synthetic fine-scale models with the most common heterogeneities: a severe thief zone, upward coarsening and downward coarsening. All simulation cases use a down-dip water injector and an up-dip oil producer. Excellent matches are obtained by history matching on the parameters of the coarse grid correlations in all cases. The flexibility of the correlations will, opposed to the restricted single-parameter Corey representation, enable a versatile, pragmatic and satisfactory upscaling for coarse grid blocks when used in combination with any well-known upscaling method. The benefit is a limited number of parameter arrays as opposed to numerous rather inconvenient tables. The proposed parametric representation of upscaled relative permeability is applicable to immiscible recovery methods in general. Implementation of the proposed three-parameter correlations of the relative permeability in the algorithm of full field simulators will overcome the representation challenges of present published upscaling methods. Upscaling of each coarse grid block individually can then be handled pragmatically, and hence provide fit-for-purpose models for field application.