Abstract
New correlations for saturated and undersaturated oil viscosity were developed for Saudi Arabian crude oil. The data consist of 79 and 71 experimental measurements of saturated and undersaturated crude oil viscosity, respectively, at reservoir conditions. Other PVT measurements above and below bubble point pressure are also included. The new correlations were developed using genetic programming approach. The new models were developed and tested using linear genetic programming (GP) technique. The models efficiency was compared to existing correlations. Average absolute relative deviation, coefficient of correlation, and crossplots were used to evaluate the proposed models, and their outputs indicate the accuracy of the GP technique and the superiority of the developed models in comparison with the commonly utilized models tested.
Highlights
Crude oil viscosity is an important physical property that controls and influences the flow of oil through porous media and pipelines
Measurements were conducted within the ranges of 72–292 °F, 132–5645 psia, and 51–3544 cu ft/bbl for reservoir temperature, bubble point pressure, and solution gas–oil ratio at bubble point, respectively
The functional form of Sutton’s was used in this study to develop the undersaturated oil viscosity correlation. They developed a crude oil viscosity model based on API gravity, temperature, and solution gas–oil ratio
Summary
Crude oil viscosity is an important physical property that controls and influences the flow of oil through porous media and pipelines. Measurements of 600 samples dataset were used to derive the correlation with pressure range of 0.0–5250 psig, solution GOR of 20–2070 scf/STB, oil gravity of 16–58 °API, and temperature of 70–295 °F They limit their correlation on data that do not have crude composition and suggest using different correlations for better accuracy if composition is available. Many correlations have been proposed to calculate the undersaturated oil viscosity These correlations predict viscosities from available field samples including reservoir temperature, oil API gravity, solution gas–oil ratio, pressure, and saturation pressure. The functional form of Sutton’s was used in this study to develop the undersaturated oil viscosity correlation They developed a crude oil viscosity model based on API gravity, temperature, and solution gas–oil ratio.
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