Hydrocarbon fields that contain non-associated gas, such as gas condensate, are highly valuable in terms of production. They yield significant amounts of condensate alongside the gas, but their unique behavior presents challenges. These reservoirs experience constant changes in composition and phases during production, which can lead to condensate blockage near wells. This blockage forms condensate bridges that hinder flow and potentially decrease gas production. To address these challenges, engineers rely on numerical simulation as a crucial tool to determine the most effective project management strategy for producing these reservoirs. In particular, relative permeability curves are used in these simulations to represent the physical phenomenon of interest. However, the representativeness of these curves in industry laboratory tests has limitations. To obtain more accurate inputs, simulations at the pore network level are performed. These simulations incorporate models that consider alterations in interfacial tension and flow velocity throughout the reservoir. The validation process involves reproducing a pore network flow simulation as close as possible to a commercial finite difference simulation. A scale-up methodology is then proposed, utilizing an optimization process to ensure fidelity to the original relative permeability curve at a microporous scale. This curve is obtained by simulating the condensation process in the reservoir phenomenologically, using a model that captures the dependence on velocity. To evaluate the effectiveness of the proposed methodology, three relative permeability curves are compared based on field-scale productivities and the evolution of condensate saturation near the wells. The results demonstrate that the methodology accurately captures the influence of condensation on well productivity compared to the relative permeability curve generated from laboratory tests, which assumes greater condensate mobility. This highlights the importance of incorporating more realistic inputs into numerical simulations to improve decision-making in project management strategies for reservoir development.
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