Water-alternating-gas (WAG) flooding has been successfully used as development alternative providing frontal mobility control for better conformance, potential reduction of residual oil saturations to water, particularly when miscibility is achieved, and relative permeability changes as result of the cyclic injection. Forecasting performance of the WAG process often involves the use of numerical simulation models that allow the inclusion of capillary, viscous, gravity forces, compositional and hysteresis onto the frontal movement, recovery and injection requirements. It is not uncommon to encounter models that are not necessarily built to address the specific challenges of the WAG displacement and thus require validation and modifications to improve consistency and predictive power. WAG processes are traditionally characterized through a series of laboratory and field observations, a process that starts with corefloods where injection volumes, sequence and water-gas proportions (among others) are optimized and its results are used to calibrate the necessary parameters to represent the WAG process in the dynamic models by simulating the laboratory experiments. These core-level calibrated parameters are often directly used without modification even though the parameters are unique to the scale at which they were calibrated. Investigation into practical translation and use of these core-level parameters on pilot and full field numerical models is the main objective of this paper. This paper builds on the results of previous work which described a multi-stage upscaling process by introducing a series of 1D, 2D and 3D models of varying resolution ranging from core scale to expected full field resolution. The models are built to represent average well spacing as well as reproduce expected frontal advancement. The high-resolution models are used as reference since they are closest to the core scale and the results of the different numerical resolutions are used to determine upscaling requirements (concentrated on immiscible water-alternating-gas - iWAG) as well as investigate the impact and limitations on the magnitude of the upscaling. A realistic full field model is used to validate the impact of the upscaled iWAG parameters on different model resolutions. Results of the investigation were in line with previous work (Talabi et al. 2019) identifying significant deviations in the oil, water and gas production for horizontal grid resolutions beyond 50ft where numerical dispersion and dilution accounted for an early water arrival and subsequent decrease trapping of the non-wetting phase. Oil recovery was consistently underestimated by 2-8% as the grid resolution increased. The upscaling strategy proposed involves the modification of trapping parameters to account for the numerical dilution effect: increase of non-wetting phase relative permeability reduction factor and three-phase wetting phase relative permeability was sufficient to reproduce the overall fine scale mobility (to overcome dispersion/dilution effects). Acceptable calibrations that allow coarse models to reproduce the fine scale results were obtained on the 1D/2D/3D models. As expected, the magnitude of the WAG parameter changes was process and heterogeneity dependent (Moreno et al. 2011) requiring fine tuning as model complexity increased. While the complexity, heterogeneity and fluid dependence of the WAG process is recognized, a multi-stage upscaling approach as described in this paper, is offers an opportunity to better understand the process drivers and design a practical upscaling strategy suitable to accommodate the full field operation and avoid underprediction of WAG performance.

Immiscible water-alternating-gas (iWAG) flooding is often considered as a tertiary recovery technique in waterflooded or about-to-be waterflooded reservoirs to increase oil recovery due to better mobility control and potentially favorable hysteretic changes to phase relative permeabilities. In such cases, typically, reservoir simulation models already exist and have been calibrated, often modifying saturation functions during the history matching stage. However, to utilize such models in forecasting iWAG performance, additional parameters may be required. These can be acquired by simulation of WAG coreflood experiments. While in many published cases, the parameter values obtained from matching experimental results are used without modification, this may not be advisable since the parameters are only valid at the core scale at which they were obtained. This paper discusses the challenge of systematically upscaling WAG parameters obtained at core scale to an existing full field model. In this work, we use a multi-stage upscaling process from core scale to full field scale. The first stage uses a core scale model to match ‘representative’ core flood experiments and obtain WAG parameters. The second uses a well-to-well high-resolution 1D section of the full field model populated using gridblocks of core size to generate ‘reference’ WAG performance using the unaltered WAG parameters obtained from core. The third stage uses a similar 1D model but populated using gridblocks at full field model resolution to match the results from the reference model while adjusting the WAG parameters as little as possible. Finally, a model using the full field model resolution as well as the full field relative permeability functions which, it is assumed, have been tuned to match the history and account for dispersion is used to match the reference model results and obtain final upscaled WAG parameters. The upscaled WAG parameters obtained at the end of this multi-stage process can be used at the field scale. This process allows clear quantification of the uncertainty associated with the upscaling process. Simulations at the third stage showed that once the full field to core scale grid size ratio exceeded a certain point (2500:1), there was a marked increase in the difference between upscaled and reference model results. It was found that if WAG parameters were changed in the full field model resolution model in order to match recovery results in the reference model, Land's parameter could change by up to 10% and relative permeability reduction factor could increase by up to 30% although it is expected that this will vary from case to case. It is therefore recommended to identify and use full field model resolutions to as close to the threshold as possible. The practice of using the core scale iWAG parameters in the full field model directly could under-estimate actual recovery, and overestimate injectivity. When considering the WAG mechanism alone, the value of the recovery underestimate increasing with pore volumes injected and, in our case, by up to 7% after injecting 1 pore volume of fluid. This multi-stage simulation approach helps identify the adjustments required and uncertainties associated with simulating iWAG flooding in reservoir models. This approach utilizes options widely present in commercially available finite difference simulators, addresses the challenge of utilizing existing pseudo functions and provides a practical methodology through which iWAG performance forecasting can be improved.