High viscosity is a major concern in the recovery of heavy oil and bitumen. Viscosity reduction could be achieved by mixing bitumen with solvents. Cragoe (1) and Shu (2) have developed widely used methods for liquid mixture viscosity predictions. However, in these two models, the viscosities or densities of the heavy oil/bitumen and solvents have to be known at some reference condition.
Low field nuclear magnetic resonance (NMR) relaxometry is an effective, non-destructive alternative for determining the petrophysical properties of oil reservoirs. It has also been shown to successfully predict the viscosity of conventional oils, heavy oils, and mixtures of oils with solvents.
In this paper, a regression model of experimental data, Cragoe(1), Shu (2), and NMR models are compared with experimental data which were obtained from four heavy oil/bitumen samples mixed with six solvents in different ratios. NMR-based predictions are found to be similar to those of the Shu (2)model and superior to the predictions of the Cragoe (1) model.
Viscosity and density reduction of a heavy oil or bitumen could be achieved by mixing it with a solvent. The information about the viscosity of a heavy oil/bitumen-solvent mixture is vital for designing solvent floods and for input into reservoir simulators, both for recovery processes and reserves assessment. Several correlations have been proposed for estimating the viscosity of a mixture of liquids. Cragoe(1) and Shu (2) have developed two widely-used methods for mixture viscosity predictions. In both of the models, viscosities of the heavy oil or bitumen and solvents have to be known for prediction. Sometimes, it is hard to measure the viscosity accurately using conventional viscometers when it is too high or too low, and a conventional viscometer is not a convenient method for in situ measurements.
Low field nuclear magnetic resonance (NMR) relaxometry is an effective, non-destructive alternative for determining the petrophysical properties of an oil reservoir. It was also shown to successfully predict the viscosity of conventional oils (3) and heavy oils (4). The greatest advantage of NMR is its potential to translate these density and viscosity measurements to in situ measurements, which could be implemented in a logging tool, allowing density and viscosity to be estimated without having to extract oil samples in the lab. The NMR viscosity model is especially significant for use in designing a solvent injection process for heavy oil recovery.
Four oils were used in the solvent experiments (5). They were from Peace River, Cold Lake, Edam, and Atlee Buffalo, and have viscosities of 670,000 mPa’s, 130,000 mPa’s, 14,000 mPa’s, and 6,000 mPa?s, respectively, at 25 °C. Kerosene, toluene, naphtha, heptane, hexane, and pentane were added to the oils in several predefined mass fractions: 100% oil, 99%, 96%, 93%, 90%, 85%, 80%, 70%, 50%, 30%, and 0% (100% solvent). The samples were slightly heated and mixed by stirring, and the resulting solventoil mixtures were cooled. NMR spectra were measured at 25 °C using an Ecotek FTB bench top relaxometer.