Optimum field development strategy requires good knowledge of anticipated well performance and future flowing condition variation. This practice involves continuous monitoring of surface facility network, wells, and reservoir. Thus, it is crucial for the petroleum engineer to possess the appropriate tools to efficiently forecast well behavior, design artificial lift equipment and stimulation treatments, forecast production, and improve the entire production system optimization. Inflow performance relationship (IPR) is one of the vital tools required to monitor well performance. Currently used inflow performance relationship models are idealistic in nature, mainly developed for homogeneous reservoirs, and not suitable for multi-layer systems with different permeabilities. Consequently, the available IPR relationships do not provide accurate performance of such reservoirs. Thus, there is an urgent need for new realistic IPR models that describe the actual reservoir inflow performance behavior more efficiently than t he available models.
This study investigates the effects of reservoir heterogeneity on IPR curves for wells producing from multi-layer solution-gas drive reservoirs. To achieve the desired objectives a stochastic simulation algorithm known as simulated annealing was used to generate various permeability realizations among the stacked layers. The generated data were then thoroughly scrutinized and two simple yet accurate empirical IPR models were developed for heterogeneous two and multi-layer solution-gas drive reservoirs.