Oil Formation Volume Factor Determination Using a Rigorous Approach

PVT properties of reservoir fluids are key parameters to a series of calculations such as reserve and production, inflow performance and material balance calculations. The determination of these properties is a complex problem, because laboratory-measured properties of fluid samples are only available from limited and isolated well locations and/or intervals. Several models have been developed to relate these properties to other measures which are relatively abundant. These models include empirical correlations, statistical regression and intelligent systems. In this paper, a new model for prediction of oil formation volume factor has been developed using more than 1100 experimental data series collected from different geographical locations worldwide. To this end, Least Square Support Vector Machine (LSSVM) modeling optimized with coupled simulated annealing (CSA) tool was used to develop a reliable model for prediction of oil formation volume factor. The developed model was compared with other published models, and the results indicated that the developed model is more accurate, reliable and superior to other existing correlations.

Keywords:

Oil formation volume factor , least square support vector machine , Crude oil