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Excessive water production from hydrocarbon reservoirs is considered as one of major problems, which has numerous economic and environmental consequences. Polymer-gel remediation has been widely used to reduce excessive water production during oil and gas recovery by plugging high permeability zones and improving conformance control. In this paper, we investigate the performance of a HPAM/PEI (water-soluble Hydrolyzed PolyAcrylaMide/PolyEthyleneImine) polymer-gel system for pore space blockage and permeability reduction for conformance control purpose. First, the gel optimum composition, resistance to salt and long life time are determined using bottle tests as a standard method to specify polymer-gel properties. Then the performance and stability of the optimized polymer-gel are tested experimentally using coreflood tests in sandpack core samples. The effects of different parameters such as gel concentration, initial permeability of the cores, and formation water salinity on the final permeability of the cores are examined. Finally, the gel flow-induced local porosity changes are studied in both a sandpack core and a real carbonate sample using grayscale intensity data provided from 3D Computed Tomography (CT) images in pre- and post-treatment states. The results show that the gel system has a good strength at the middle formation water salinity (in the range of typical sea water salinity). In addition, despite a higher performance in high permeability cores, the gel resistance to degradation in such porous media is reduced. The CT images reveal that the initial porosity distribution has a great influence on the performance of the gel to block the pore space.

The detailed geological fine grids are upscaled to create reliably sized simulation coarse models to solve flow equations in a more efficient way. Any upscaling process results in a loss of accuracy, along with an increase of errors. Numerical dispersion, heterogeneity loss, and connectivity misrepresentation are responsible for the upscaling errors. Recognizing the source of each error, and the behavior of influential factors through upscaling process could provide an optimum level of upscaling and an evaluation of upscaling methods’ accuracy. Despite the importance of upscaling error, little attention has been paid to this subject. This paper represents a rigorous analysis of the heterogeneity loss behavior associated with the relative permeability contrast and the mobility ratio under a waterflooding process. For this purpose, heterogeneous fine grid models are constructed by the fractional Brownian motion process. The models are upscaled by three upscaling factors. The models achieved are implemented to eliminate the impact of numerical error among upscaling errors in order to focus strictly on heterogeneity loss. Water–oil displacement simulation is then performed on fine and corresponding refined upscaled models at three different ratios of relative permeabilities and mobility ratios. In the next stage, the relation between flow performance error and heterogeneity loss is investigated by the heterogeneity loss plot. The slope of this plot provides the reservoir engineer an insight to evaluate the performance of upscaling methods and the behavior of the influential factors on upscaling errors. Moreover, by using the heterogeneity loss plot for each ratio, a limit of coarsening is presented. Based on the results, the heterogeneity loss error is affected more by the mobility ratio contrast than the relative permeability difference. Also, it is demonstrated that water-wet reservoirs with light oil are more sensitive to the level of upscaling.