Upscaling reservoir properties for reservoir simulation is one of the most important steps in the workflow for building reservoir models. Upscaling allows taking high-resolution geostatistical models (10 7 -10 8 grid blocks) to coarse scale models (10 4 -10 5 grid blocks), manageable for reservoir simulation, while retaining the geological realism and thus effectively representing fluid transport in the reservoir 1,2 . This work presents a study of the effectiveness of different available techniques for permeability upscaling and the implementation of a new technique for upscaling of relative permeability curves based on the numerical solution of a two-phase system and the Kyte and Berry method 3 .The reference fine scale model considered in this study is a conceptual fluvial reservoir based on the Stanford V model 4 . The reference fine scale isotropic and locally heterogeneous permeability distribution was upscaled to different upscaling ratios by means of analytical (static) and numerical single-phase (pressure solver, dynamic) techniques. Two-phase flow simulations were performed on the reference fine grid and upscaled models using a comercial black-oil simulator. Arithmetic, harmonic, and geometric averages were defined for static upscaling of the permeability distribution. The dynamic upscaling process considered one-phase and two-phase upscaling. One-phase upscaling considered upscaling of the permeability distribution and two-phase upscaling considered upscaling of the permeability distribution and relative permeability curves.Flow simulation results for waterflooding in the coarse scale model indicated relevant discrepancies with the fine grid re-sults. Compared to fine-scale, flow results of the single-phase upscaling process indicated that the coarsest upscaled models did not match the water breakthrough times, water cut values, or well pressures from the reference model. The finer upscaled models reproduced the reference results more accurately than the coarser models. The two-phase dynamic upscaling technique implemented in this work resulted in the best match with the flow simulation results of the fine grid model. Results show that the most accurate upscaling scheme should be defined using the two-phase dynamic upscaling technique on the model with the smallest upscaling ratio. fax 01-972-952-9435.U.

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Use of numerical models to characterize and evaluate reservoir potential is an industry wide practice, with increasingly more development decisions being substantiated by finite difference models. Advances on hardware and software, along with the ability to effectively incorporate accurate process physics, makes simulation a robust tool for field development decisions, particularly on complex operations such as enhanced oil recovery and/or reservoirs with challenging heterogeneity and pore structures. Use of these models does not come without its challenges where data requirements (and use of special characterization both at lab and field level) increase as does the reservoir characterization granularity and thus model sizes. Unsurprisingly the increase of model precision and data requirements amplifies non-uniqueness of the numerical solutions obtained during any field evaluation including field development planning (FDP). Incomplete/inconsistent datasets pose a further challenge to the accuracy (and arguably risk) of the forecasts by introducing further uncertainty on the process characterization. Use of complementary technology such as digital rock, that would enable mitigate impact of such uncertainties in a timely manner -either at field or laboratory level, is thus highly desirable particularly when dealing with enhanced oil recovery. Compounding the non-linearity effect of the EOR agent characterization is the effect of the augmented numerical artifacts (dispersion, dilution, etc) of which complex chemical implementations are prone to, making the upscaling process from laboratory dimensions to field more complex. This paper complements our previous investigation on the use of digital rock solutions and multi-scale upscaling and is addressing two complementing topics: Use of multiscale digital rock technology for field development – using a case study to illustrate the use of DR on field appraisal complementing otherwise unsampled facies, using a multi-nested approach to reconcile DR observations at different plug scalesEvaluate the impact of finite-difference numerical simulation grid on the surfactant injection performance- highlighting limitations and challenges of existing models as well as proposing potential upscaling alternatives. It is our intention to further reconcile digital rock upscaling with other EOR methods such as polymer/CO2 injection and of course surfactant. While we were able to highlight the caveats of upscaling on complex chemical floods we continue to investigate and design a solution that would encompass combination of chemicals (surfactant, alkaline and polymer) as well as handle of concentration/salinity changes.