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Abstract
Carbonate reservoirs hold more than 60% of the world's oil and 40% of the world's gas reserves. These reservoirs are characterised by geological heterogeneity, petrophysical complexity, presence of naturally fractures, and mixed wettability, all of which contribute to significant uncertainty in volumetric estimation and fluid flow behaviour within the reservoir. In this thesis, a comprehensive 3D multiple deterministic scenario workflow was applied to compare and contrast how modelling decisions and geological uncertainties influence this reservoir's volumetric estimates and flow behaviour. Specifically, the uncertainties associated with the presence of fractures, the approach to reservoir rock type, and the modelling of the initial hydrocarbon distribution were examined. This workflow was applied to one of the giant complex carbonate reservoirs known to be fractured with a thick transition zone in the Middle East. The most significant findings of this work demonstrate that even minor changes in modelling decisions and reservoir rock typing have a substantial effect on the saturation model, resulting in up to a 28% change in STOIIP estimates, which may potentially mask the effect of other geological uncertainties. These models were validated using repeated and randomised blind tests. Such uncertainties must be carried forward in future reservoir management decisions and when estimating reserves. Additionally, some of these reservoir models led to significantly improved history match, especially for wells located in the transition zone of the reservoir. The best history matches were obtained once sparse, fault-controlled fractures were included in the reservoir model, using effective medium theory. The presence of fractures specifically improved the history matching quality for wells located close to the faults; these wells were very difficult to match in the past as fractures were not considered by the operator. This thesis demonstrates that a multi-deterministic scenario workflow is key to exploring the appropriate range of geological uncertainties and that, equally importantly, the impact of different modelling decisions (i.e., interpretation of the top structure, geostatistical parameters, reservoir rock type approach, saturation approach, and presence of fracture) must be accounted for when quantifying uncertainty during reservoir modelling. This is particularly applicable to giant carbonate reservoirs, where relatively minor changes in the workflow and data interpretation influence reserve estimates and subsequent history matching and forecasts.
