During the history matching, attentions are shifted from the structural map and focus are on the dynamic properties such as relative permeability data, saturation end points and Pressure-Volume-Temperature (PVT) information. However, structural maps can inherit huge uncertainty which can affect the dynamic behaviour of the reservoir. The objective of this study is the presentation of an approach for quantifying uncertainties in production forecast by incorporating uncertainty inherent in structural maps. Three static models (a “Low”, “Mid” and “High” cases) were developed, history matched using traditional method and used for production forecast. Two (2) possible alternatives (replicated and conventional) were considered for uncertainty analysis. This yielded four (4) reservoir proxies using experimental design techniques. Uncertainty was quantified using validated proxies with Latin hypercube sampling in a Monte Carlo simulator. Conventional and replicated approach yielded non unique answer. Replicated method which assume equal probability for the three model cases and incorporated them in the design offeres a more realistic answer. The analysis revealed with 90% certainty that at least a normalized reserve figure of 0.91 will be realized and 10% confidence that at most reserve figure of 1.039 will be realized. The method is recommendable for developing new non-complex reservoirs/fields where subsurface data acquisition is a challenge.
Key words: Uncertainty quantification, structural map, design of experiment, multiple realizations, response surface model, history matching.
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