| dc.description.abstract | The inflection point temperature of rheology (IPTR) of heavy oil transforming from a non-Newtonian fluid into a Newtonian fluid is a key parameter in the steam huff- and-puff process. It is particularly relevant in terms of optimizing injection parameters, calculating the heating radius, and determining well spaces. However, the current approach exhibits obvious shortcomings, such as the randomness of the selected tangent line and inadaptability for extra-heavy oil with high viscosity. For extra-heavy oil, the absolute error between the predicted and experimental values obtained using the tangent method has been reported to be between 15.6 °C and 16.9 °C with a relative error of between 17.4% and 18.8%. Therefore, this paper presents a novel method for calculating IPTR using viscosity–temperature data. The approach is based on the Arrhenius equation and quantitatively evaluates the IPTR according to the inflection point of the apparent activation energy. The IPTR values of four heavy-oil samples obtained from the Bohai Oilfield in China were quantitatively predicted according to viscosity–temperature data using the proposed method. The method's accuracy was verified by a series of rheological investigations on samples obtained from two heavy-oil wells. A regression of the rheological equations was performed in which 200 and 625 data points were tested, respectively, via regression to different temperatures, and the IPTR values of the different samples were obtained. The values of 75 °C and 100 °C obtained from a significant volume of experimental test data agreed well with the predicted values of 79 °C and 100 °C calculated by the proposed method. Additionally, the new method was used to predict IPTR according to the published viscosity–temperature data of ten heavy-oil samples from the Shengli Oilfield. Again, a good correspondence was found, and mean absolute and relative errors of 3 °C and 4.6%, respectively, were reported. Therefore, the proposed model was confirmed to improve the prediction accuracy of the existing method and provided a new method for calculating the IPTR of heavy oil. | |
