An Integrated Method for Forecasting Well Deliverability in Gas Condensate Reservoirs with Bottom Aquifer Drive

Abstract

Gas condensate reservoirs constitute a significant portion of global hydrocarbon reserves. In these reservoirs, liquids develop in the pore space once bottomhole pressure falls below dew point. This results in the formation of a liquid bank near the wellbore region which decreases gas mobility, which then reduces gas inflow. In such complex reservoirs, it is important to correctly describe PVT impacts, adjustments to well test analysis and inflow performance, and then combine all effects in the reservoir analysis. The literature contains many references to individual adjustments of PVT analysis, well testing, or inflow performance for gas condensate reservoirs, but few studies demonstrate the complete workflow for reservoir evaluation and production forecasting in gas condensate fields. This research uses a field case study to demonstrate an integrated workflow for forecasting well deliverability in a gas condensate field in North Africa. The workflow incorporates a description of the retrograde behavior that impact the well deliverability. The workflow begins with the interpretation of open-hole log data to identify the production interval net pay and to estimate petrophysical properties. A compositional model is developed and matched to actual reservoir fluids. Several gas condensate correlations are used to obtain the gas deviation factor and gas viscosity in order to count the change in gas properties with respect to pressure. Transient pressure analysis is described and used to identify reservoir properties. Inflow performance relationships (IPRs) are analyzed using three types of back pressure equations. The workflow integrates all data in a numerical simulation model, which includes the effect of bottom water drive. Results show that in this field case study, reservoir behavior is composite radial flow with three regions of infinite acting radial flow (IARF). Using compositional simulation, it is found that the fluid sample for this field is a lean gas condensate since the liquid drop-out represented 1% of the maximum liquid drop-out. In addition, liquid drop-out increases by 0.1% for every 340 psi drop in reservoir pressure, which reduces the AOF by 3.4%. The results provided in this case study demonstrate the importance of an integrated workflow in predicting future well performance in gas condensate fields. The study demonstrates how to implement the workflow in managing or developing these types of reservoirs.