An Integrated Model for History Matching and Predicting Reservoir Performance of Gas/Condensate Wells

Summary The depletion performance of gas/condensate reservoirs is highly influenced by changes in fluid composition below the dewpoint. The long-term prediction of condensate/gas reservoir behavior is therefore difficult because of the complexity of both composition variation and two-phase-flow effects. In this paper, an integrated model was developed to simulate gas-condensate reservoir/well behavior. The model couples the compositional material balance or the generalized material-balance equations for reservoir behavior, the two-phase pseudo integral pressure for near-wellbore behavior, and outflow correlations for wellbore behavior. An optimization algorithm was also used with the integrated model so it can be used in history-matching mode to estimate original gas in place (OGIP), original oil in place (OOIP), and productivity-index (PI) parameters for gas/condensate wells. The model also can be used to predict the production performance for variable tubinghead pressure (THP) and variable production rate. The model runs fast and requires minimal input. The developed model was validated by use of different simulation cases generated with a commercial compositional reservoir simulator for a variety of reservoir and well conditions. The results show a good agreement between the simulation cases and the integrated model. After validating the integrated model against the simulated cases, the model was used to analyze production data for a rich-gas/condensate field (initial condensate/gas ratio of 180 bbl/ MMscf). THP data for four wells were used along with basic reservoir and production data to obtain original fluids in place and PIs of the wells. The estimated parameters were then used to forecast the gas and condensate production above and below the dewpoint. The model is also capable of predicting reservoir pressure, bottomhole flowing pressure, and THP and can account for completion changes when they occur.