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PVT correlations of Indian crude using support vector regression
Published in
Volume: 23
Issue: 11
Pages: 5483 - 5490
Correlations for bubble point pressure, solution gas-oil ratio, oil formation volume factor (for both saturated and undersaturated crude) and viscosity (for both saturated and undersaturated crude) have been developed for Indian crude using support vector regression (SVR). Detailed comparisons have been made with various important correlations currently available in the literature. Radial basis function (RBF) kernel was used along with ε-insensitive loss function for developing the SVR models. The model hyperparameters were optimized using a combination of grid search and Nelder-Mead simplex algorithm. The quadratic programming (QP) problem resulting from the SVR formulation was solved using sequential minimal optimization (SMO). It was found that the developed models outperformed most other existing correlations by giving significantly lower values of average absolute relative error for the parameters studied. This study shows highly favorable results that can be integrated in most reservoir modeling software. © 2009 American Chemical Society.
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