Modeling Miscible WAG Injection EOR in the Magnus Field
- M. Haajizadeh (BP) | R. Narayanan (BP) | D. Waldren (Consultant)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Simulation Symposium, 11-14 February, Houston, Texas
- Publication Date
- Document Type
- Conference Paper
- 2001. Society of Petroleum Engineers
- 5.5.8 History Matching, 4.6 Natural Gas, 5.4 Enhanced Recovery, 5.6.5 Tracers, 5.1 Reservoir Characterisation, 5.1.5 Geologic Modeling, 5.2.2 Fluid Modeling, Equations of State, 5.3.2 Multiphase Flow, 5.4.2 Gas Injection Methods, 5.4.1 Waterflooding, 5.5.3 Scaling Methods, 5.3.4 Reduction of Residual Oil Saturation, 3.1.6 Gas Lift, 5.4.9 Miscible Methods, 4.3.4 Scale, 4.1.2 Separation and Treating, 1.2.3 Rock properties, 5.2.1 Phase Behavior and PVT Measurements, 5.5 Reservoir Simulation, 4.1.4 Gas Processing
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The viability of miscible WAG injection as an EOR scheme for the Magnus reservoir is under consideration. Performance prediction and optimization under this type of recovery mechanism, in which the residual oil is usually recovered by a multi-contact miscible (MCM) process, rely mostly upon compositional simulation. Unfortunately, numerical dispersion effects, associated with large grid blocks required in field scale compositional simulation of MCM processes, can result in erroneous phase behavior. Reduction of dispersion to acceptable levels may require very small grid blocks, implying model sizes that exceed the capacity of current conventional computer installations. Thus, full field compositional models are not practical for reliable field-wide benefit predictions.
This paper presents a systematic procedure that we successfully employed for prediction of field wide performance and recovery benefit of miscible WAG injection for the Magnus reservoir. The procedure involves an extension of the upscaling technique proposed by Fayers et al . It starts with a 3D fine grid compositional sector model of a small representative element of the reservoir. Then, this reference model is upscaled to block sizes corresponding to those in the Magnus full field model (FFM), using the single-phase half-cell upscaling technique. The upscaled model employs the Todd and Longstaff (T&L) formulation [1,2] for simulating MCM displacement and three-pseudo components for representing phase behavior. The PVT, solvent equilibrium constants and miscibility pressure vs. composition tables are developed through matching with a calibrated 12-component equation of state (EOS) and 1D slim tube simulations, for a wide range of pressure and composition. The PVT treatment also allows for vaporization of oil by the contacting gas.
To calibrate the model, the upscaled transmissibility values had to be further adjusted in order to match the reference single-phase pressure/rate performance for several horizontal and vertical flow orientations. The base waterflood performance matching was achieved for a couple of potential well orientations by adjusting water-oil relative permeability curves. The final stage involved determining the T&L mixing parameters through calibration of MCM WAG displacement performance with the reference fine grid compositional model.
This approach led to a set of T&L mixing parameters, which result in a very encouraging match between the upscaled and the reference model. Calculated WAG recovery is more sensitive to the viscosity rather than density mixing parameter, indicating a moderate tendency for gas gravity override. Further sensitivities were performed to examine the robustness of the calibrated upscaled model against variations in operating parameters. The results confirm that the upscaled model satisfactorily matches the reference model in terms of variations of the benefit with slug size and WAG ratio.
The determined T&L mixing parameters were then implemented with confidence in the Magnus T&L FFM for predictions of field-wide MCM WAG benefit, returned gas (injected gas produced) volume and composition, and water and gas lift gas requirements post EOR.
We also discuss impacts of various uncertain parameters on the performance of MCM WAG injection, which were investigated using the calibrated upscaled model, taking advantage of about 1000 times gain in CPU time compared to that for the reference fine grid compositional model.
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