Viscosity and density are important physical properties of crude oil. However, no practical theory exists for the calculation of these properties for heavy oil at elevated temperatures. The principal objective of this paper is to obtain exact models that can successfully predict these two important fluid properties covering a wide range of temperatures. In this study, heavy oil density was predicted from API and temperature, and then the predicted values of the densities were used in the second step to develop the viscosity correlation. A total of 30 heavy oil samples of different API gravities ranging from 11.7 to 18.8 were tested. Viscosity and density were measured in the temperature range from 20 to 160°C. The accuracy of the experimental density data was determined using Standing and Katz method. Published correlations were also used to evaluate the experimental viscosity data. The comparison between the experimental data and the predicted values indicated that the proposed model successfully predicted the experimental data with an average absolute relative error of less than 8 % and correlation coefficients (R 2 ) of 0.97 and 0.92 at normal and high temperatures, respectively. The proposed model and the literature models were tested on heavy oil samples. It was found that it is not possible to generalize a correlation for the heavy oil viscosity using only API and temperature. However, the proposed model significantly minimizes the relative error and increases the correlation between the predicted and experimental data compared with other published methods.
Viscosity and Density are important physical parameter of crude oil, closely related with the whole processes of production and transportation, and are very essential properties to the process design and petroleum industries simulation. As viscosity increases, a conventional measurement becomes progressively less accurate and more difficult to obtain. According to the literature survey, most published correlations that are used to predict density and viscosity of heavy crude oil are limited to certain temperatures, API values, and viscosity ranges. The objective of present work is to propose accurate models that can successfully predict two important fluid properties, viscosity and density covering a wide range of temperatures, API, and viscosities. Viscosity and density of more than 30 heavy oil samples of different API gravities collected from different oilfield were measured at temperature range 15 o C to 160 o C (60 o F to 320 o F), and the results were used to ensure the capability of proposed and published correlations to predict the experimental viscosity and density data. The proposed correlation can be summarized in two stages. The first step was to predict the heavy oil density from API and temperature for different crudes. The predicted values of the densities were used in the second step to develop the viscosity correlation model. A comparison of the predicted and actual viscosities data, concluded that the proposed model has successfully predict all data with average relative errors of less than 12% and with the correlation coefficient R 2 of 0.97, and 0.92 at normal and high temperatures respectively. Meanwhile, the results of most of the available models has an average relative error above 40%, with R 2 values between 0.19 to 0.95. These comparisons were made as a quality control to confirm the reliability of the proposed model to predict density and viscosity values of heavy crudes when compared with other models.
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