A Holistic Data Driven Approach for Condensate Recovery Factor Estimation in Gas Condensate Reservoirs
Authors: Akram Agha Hassan , Khan Waqar Ali , Zubair Talha , Shah Abdur Rahman , Mirza Hamza Ali , Zahid Salman , Yousuf Muhammad , Memon Imtiaz Ali 
Published: November 2020

Abstract
Gas-condensate reservoirs exhibit complex multi-phase flow behavior below saturation pressures resulting from compositional variations. Below saturation pressure, condensate starts dropping-out within the reservoir and eventually develops a bank in the near wellbore region; effectively reducing the relative permeability to gas flow. As a result, production of main phase (gas) decreases with development of this bank while condensate is left behind in the reservoir. Since, reserves estimation is a part of the development plans of all fields, it is important to account for condensate drop-out while deriving a condensate recovery factor during the initial stage of the life of a reservoir. Otherwise a high condensate recovery factor (if assumed equal to or close to that of gas phase) might result in unrealistic optimistic cash flow projections. Given the importance of condensate recovery factor estimation, a data driven analytical method has been developed and will be discussed in detail in this paper; while overcoming the limitation of available data for green fields.
An analytical methodology has been developed for calculation of condensate recovery factor in gas condensate reservoirs in the absence of a constant volume depletion (CVD) study laboratory report. The method uses either a linear or a non-linear correlation-based relationship between condensate drop-out and pressure. This enables derivation of an equation for calculation of condensate recovery factor while incorporating critical parameters such as dew point pressure, initial and abandonment pressures and condensate gas ratios (CGRs) at initial and abandonment conditions. A stepwise procedure will be described to derive all these parameters with limited available data in the early stages of the life of reservoir.
The methodology adopted was applied to more than 30 green and brown gas condensate fields with varying CGR's. For a few mature fields, results derived from the proposed methodology were compared with recovery factors estimated from numerical simulation models. Results of both approaches appeared to be in a good agreement with an accuracy of +/−10%. As expected, recovery factors derived assuming a simple linear decline of CGR with pressure were less accurate than those calculated using a non-linear correlation-based decline of CGR with pressure. For richer gas condensate fields with high compressibility factors, the z-factor was incorporated with pressure in the form of P/z, which resulted in a more accurate estimation of recovery factors. A comparison has been made where recovery factors are estimated from the described approach and the other reference approaches; and conclusions drawn from these comparisons are discussed.
Various approaches have been used historically for condensate recovery factor estimation while relying heavily on a good amount of data available. A simple analytical approach has been discussed which mitigates the impact of poor data availability especially in green fields and yet can yield useable condensate recovery factor calculations. This enables better reserve estimation of condensates in gas condensate reservoirs in early stages of life of reservoirs, while leading to efficient and realistic field development plans in futures.