An adequate knowledge of any reservoir fluid PVT properties is essential for most types of petroleum calculations. These calculations include amount of oil in the reservoir, production capacity, variations in produced gas-oil ratio during the reservoir's production life, calculation of recovery efficiency, reservoir performance, production operations and the design of production facilities. PVT properties can be measured experimentally by using collected bottom-hole or surface samples of crude oils. But, the experimental determination of PVT is time consuming and very costly. In addition, even with the availability of PVT analyses, it is often necessary to extrapolate the data to field and/or surface conditions through the use of empirical correlations. Furthermore, geological and geographical conditions are considered very critical in the development of any correlation. But, universal correlations are difficult to develop. That is why correlations for local regions, where crude properties are expected to be uniform, is a reasonable alternative. In this study, experimental PVT data for North and South Oman crudes, statistical and artificial neural network (ANN) analyses are used to develop reliable PVT correlations. Comparisons with previously published correlations are presented.
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