Ogbuagu, Frank (Chevron Nigeria Limited) | Afolayan, Femi (Chevron Nigeria Limited) | Esan, Femi (Chevron Nigeria Limited) | Obot, Nsitie (Chevron Nigeria Limited) | Adeyemi, Ganiyu (Chevron Nigeria Limited) | Okpani, Olu (Chevron Nigeria Limited)
This paper summarizes the strategy adopted in the development of two thin oil rim reservoirs in Okan Field, Offshore Niger Delta, Nigeria.
Its objective is to elucidate the strategy, engineering analyses, subsurface assessment and production procedures set in place to optimally develop the reservoirs.
Both reservoirs have oil thickness of <30 ft with gas thickness of >100 ft. The adopted development strategy for the two reservoirs involves the drilling of 4 wells, 2 in each reservoir, to drain the remaining oil reserves, prior to gas development.
Because of structural and fluid contact uncertainties, soft landing was incorporated into the well designs. Shale-to-shale correlation was used for accurate horizon depth prediction and detailed simulation models with local grid refinements were employed to determine optimum well orientation, landing depth, lateral length and aquifer properties. Details on their use to maximize value are shared.
While drilling, Azithrak™, a Baker Hughes tool, was used in geosteering the lateral well section to determine distance of well to nearest conductive zone as part of the oil-water contact tracking. All available data - logs, cuttings, reservoir pressures and production data - was incorporated and used to validate fluid contacts data because of the impact of landing depth relative to the fluid contacts on oil recovery. Simulation results and operational constraints were used to set acceptable production limits to ensure delivery of target reserves.
All the four wells have been successfully drilled and completed, with the wells landed successfully within the thin oil column, at the optimized distance from the fluid contacts, with the wells producing at <0.55 percent water cut. Initial production performances of the four wells are in line with static and dynamic assessment forecasts.
Lessons learned and challenges encountered during this development are also captured in this paper.