Improved oil formation volume factor (Bo) correlation for volatile oil reservoirs: An integrated non-linear regression and genetic programming approach.

Abstract In this paper, two correlations for oil formation volume factor (B o) for volatile oil reservoirs are developed using non-linear regression technique and genetic programming using commercial software. More than 1200 measured values obtained from PVT laboratory analyses of five representative volatile oil samples are selected under a wide range of reservoir conditions (temperature and pressure) and compositions. Matching of PVT experimental data with an equation of state (EOS) model using a commercial simulator (Eclipse Simulator), was achieved to generate the oil formation volume factor (B o). The obtained results of the B o as compared with the most common published correlations indicate that the new generated model has improved significantly the average absolute error for volatile oil fluids. The hit-rate (R ²) of the new non-linear regression correlation is 98.99% and the average absolute error (AAE) is 1.534% with standard deviation (SD) of 0.000372. Meanwhile, correlation generated by genetic programming gave R ² of 99.96% and an AAE of 0.3252% with a SD of 0.00001584. The importance of the new correlation stems from the fact that it depends mainly on experimental field production data, besides having a wide range of applications especially when actual PVT laboratory data are scarce or incomplete. [ABSTRACT FROM AUTHOR]