This multi-disciplinary study involved the use of parallel simulation using the same grid size as the geological model. Various production technology options for the remaining wells in a field development were investigated and the benefits of gas cycling were examined. A geological model covering an area of 40 km2 was simulated using two approaches; one using 3 levels of nested LGR's and the other using an areal upscaling, both had nearly the same number of active grid cells. The 12-component Equation-of-State ("EoS") was substituted by 5-component to optimise the run speed of the simulation, 12-component was used for investigating gas cycling. The final engineering model had 320,000 active cells and completed 1.5-year history-matching runs in 1 hr 27 min using 16 parallel 400MHz processors with 1GB RAM each.

Both methods worked well and the history was matched with minor changes to the geological model. The primary match parameters were the relative permeability curves since relative permeabilities from special core analysis at reservoir conditions were not available. Correlations from the literature were used for the original relative permeability curves. These were modified to capture the effects of near-well velocity stripping by ‘straightening’ the curves and moving the end points. Through a combination of local grid refinement (LGR) and relative permeability modifications, the effects of the condensate dropout near wellbore and the transient effects were captured. These effects reduce the wells' productivity by 40% in the first weeks of production.

In the prediction phase the full field model was used to examine, holistically, the effects and interaction of various options chosen by analytical screening. The main solutions compared were high angle (near horizontal) reservoir penetrations and hydraulically fractured wells. Hydraulic fractures were modelled using LGR to capture the behaviour of the condensate in the fractures. The high angle wells were surrounded by LGR. A large number of prediction cases were run, optimising the development scenario using stochastically derived drilling schedules. Considerations of capital allocation led to the final recommendation from the group of optimal solutions.

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