Prediction Modeling for Combination Drive Reservoir Performance

Halafawi Mohamed, Abdel Waly Abdel Waly Abdalah


Depletion performance of combination drive oil reservoirs is highly influenced by changes in reservoir rock and fluid data, relative permeability data, and PVT data of reservoir. Therefore, future prediction of combination drive oil reservoirs is difficult due to the long terms, huge equations and the sensitivity of data especially the PVT data and relative permeability data.
In this paper, an integrated analytical model was developed to simulate the combination drive oil reservoir’s performance. It couples the general material balance equation with equations for water influx, water-invaded pore volume, gas-invaded pore volume, oil and gas saturation, and fluid contacts for combination oil reservoirs. All these equations are merged and solved simultaneously with reservoir depletion stages.
A comparison with the various equations’ results for the integrated model has been developed so that it can be utilized in history match mode. This is used to estimate fluid saturation distribution after water influx and gas-cap invasion, original fluids in place, aquifer parameters and type, fluid contact levels, and effective recovery factor during gas and water aquifer movement towards the productive hydrocarbon zone in all reservoir depletion stages.
The developed model has been validated using published cases for various oil reservoirs’ conditions, resulting in a good match between published case results and developed model results for these reservoirs. After validating the model, it has been used for two Egyptian combination drive fields. The field production history has been matched and future production performance for these reservoirs was simulated.
Finally, the developed model also has the capability to predict reservoir performance for another Egyptian combination drive oil reservoir field under water and or gas injection, integrated with decline curve analysis.


Combination drive reservoirs; History match; Future performance prediction; Injection performance; Fields case studies; Prediction model

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