Assessment of Condensate Banking Growth Using Advanced Pressure Transient Analysis

Abstract

AbstractCondensate banking is a process that occurs in gas wells when the reservoir pressure goes below the dew point. The depletion process introduces an additional fluid complexity, which complicates reservoir dynamics and reduces ultimate recovery. In addition, it hinders well performance and productivity due to its growth over production time.Estimating the current extent of condensate banking and predicting its progression over time plays a major role in optimizing well performance. Using single-phase pressure transient analysis to account for different mobility regions is widely practiced across the industry. However, a non-linear model must be utilized for the conditions where more than one phase exists, such as in gas condensate reservoirs. The model should consider non-linearities such as relative permeability curves for multi-phase systems, and pressure-dependent PVT properties such as viscosity, condensate gas ratio, and fluid compressibility.Non-linear modeling provides an accurate estimation of the different characteristic regions caused by condensate banking in terms of distance, mobility, and saturation variations, ensuring proper reservoir characterization. Additionally, with the utilization of test design function, non-linear modeling predicts condensate banking development, giving a precious indication of future well and reservoir conditions. The deployment of the advanced non-linear model in the pressure transient analysis (PTA) results in reasonable estimations of condensate banking distance from these wells. Finally, the results of the non-linear method highlighted the difference when compared to single-phase models, showcasing the importance of mimicking actual well and reservoir multi-phase conditions properly.In this study, we will illustrate pressure transient analysis test designs in condensate reservoirs, highlighting the condensate banking effect on the well performance and the extent estimation of the fluid bank utilizing a non-linear modeling approach as an aid in optimizing well performance.