Abstract

Abstract This paper highlights the importance and benefits of integrating both static and dynamic data, in defining the range of structural uncertainties in a mature field in the Niger Delta Basin. Appropriate management of static and dynamic subsurface uncertainties enhances the prediction of the subsurface and improves the quality of key development decisions. Typically, structural uncertainty ranges are mostly associated with seismic and geologic data (e.g., seismic loop pick, fault positioning/geometry and velocity model for time-to-depth conversion etc.), while dynamic data (e.g., production data) are rarely considered. To model the mature ‘A-sands’ in Craig field, a subsurface uncertainty matrix was generated consisting of all identified uncertainties as well as their ranges. Low, base and high case structural and static models were built in Petrel for the ‘A-sands’ and then transferred to a dynamic simulator for history matching and to assess impact of these uncertainties on ultimate recovery. Experimental Design (ED) technique was used during dynamic modelling to integrate all the uncertainty parameters with the aim of selecting the best history-match realizations that will be used for forecasting. Initial results obtained from ED indicated acceptable history matches for the base case model, while the quality of matches for low and high case models were poor / unacceptable, suggesting a need to review the uncertainty ranges. This was further supported by a narrow range of recoveries obtained from DCA (decline curve analyses) for the producing conduits in the reservoirs. Also considering the maturity of the field (over 70 wells drilled, with Np over 30% of the oil in-place), it was pertinent to revisit the ranges Based on these informations, the uncertainty ranges were reviewed, with focus on those that have the largest impact on history match results. This paper focuses on the review carried out on the structural uncertainty - which has the largest impact on history match results - leading to smaller ranges of structural uncertainties. The reduced depth uncertainty values resulted in static models and volumetric estimates that supported historic production data for the reservoirs, producing much improved history matches.

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