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Predictive Models for Condensate Gas Ratio (CGR) – Part 1: For Western Niger Delta Region

Condensate-to-gas ratio (CGR) playsa significant role in sales potential assessment of both gas and liquid, design of the required surface processing facilities, reservoir characterization and modeling in gas -condensate reservoirs.This work aim at the use of regression method to develop Condensate gas ratio (CGR) correlations using dataset obtained from Western Niger Delta region. The formation was divided into three distinct geologic zones: Transitional Paralic, Paralic and Marine Paralic zones. The basic parameters used for the correlatio n development are: reservoir depth (ft), reservoir pressure (psia); reservoir temperature ( o

Review Of PVT Correlations For Crude Oils

Reservoir fluid physical property values constitute an integral part of the data required for comprehensive study of the reservoir and for optimal design of oil recovery and production schemes. More specifically, Pressure-Volume-Temperature (PVT) data corresponding to the reservoir fluid are needed to validate the well test property and to provide meaningful interpretation. In the absence of laboratory measured PVT data, property correlations are used for property estimation. Various PVT correlations have been published over the years, which used data from limited geographical areas, sometimes assumed to be global and differing fluid characteristics. Because of variation in the crude compositions, geographical, and petrophysical conditions of the operating environments, these correlations cannot acclaim universal applicability. This paper attempts to give comprehensive review of existing PVT correlations and models in the literature, indicating geographical region, accuracies as well as the nature of these correlations. Using these correlations from other regions would have implications such as poor fluid property estimations, poor reservoir performance studies, as well as uncertainty in reserve estimations in the Niger Delta. Keywords : PVT Correlations, PVT Data, Reservoir Fluid Properties, Fluid Property Estimation Global Journal of Pure and Applied Sciences Vol. 14 (3) 2008: pp. 331-338