چكيده به لاتين
Crude oil is a mixture of different organic compounds with different boiling points. During the oil extraction process, from extraction to processing, the hydrodynamic and thermodynamic conditions change. These changes in some cases cause problems in various sectors of the oil industry. One of the most well-known and important of these problems is asphaltene precipitation, which imposes high costs during the crude oil extraction process. Therefore, predicting the conditions of asphaltene precipitation is very important to prevent this problem. Due to the unknown structure of asphaltene, a suitable method to eliminate sediment problems is to predict and prevent the formation of sediment. The results show that thermodynamics can help us better understand the precipitation mechanism with molecular model-based equations of state, although more experimental experiments should be performed to add more detail to different thermodynamic models. Also, due to the uncertainty of the precipitation mechanism, the use of new equations and models continues. In this study, Flory-Huggins theory is combined with two PC-SAFT and Peng-Robinson equations of state. Asphaltene is also assumed to be macromolecules that have pre-aggregation properties, but the association properties of these macromolecules with each other and with other components are ignored. In this modeling, asphaltene was considered pseudo-liquid and both single-component and multi-component modes were investigated. In order to divide the asphaltene into several components, the rules of mixtures were used. Since three different normal alkanes were used for titration, it was necessary to expand the heavy cutting section of crude oil. Bubble pressure and onset pressure are also obtained for different temperatures. The most important parameter in this method is solubility; In fact, solubility can be defined as the pressure that the molecules of two substances exert on each other, which is calculated by calculating the cohesion energy. The solubility parameter was used to adjust the titration and onset pressure diagrams. This parameter for asphaltene is usually between 19-25 〖MPa〗^0.5. According to the results of this study, it can be said that the division of asphalt into several components has a very good effect on the calculation of onset pressure. This issue is clearly evident in the diagrams of both fluids. The average error obtained for predicting bubble pressure for the first sample (C1) and using the Peng-Robinson equation of state with a multi-component approach is 8% and for the PC-SAFT equation is 2.8%; Also for the second sample (Y3) and using the Peng-Robinson equation of state with a multi-component approach, it is 6.6% and for the PC-SAFT equation of state, it is 6.7%. To predict the onset pressure for the first sample and using the Peng-Robinson equation of state with single-component it is 1.4% and for the PC-SAFT equation of state is 0.7%; Also in the second sample, using the Peng-Robinson equation of state with a multi-component approach, it is 6.6% and for the PC-SAFT equation of state, it is 6.7%. In the titration for the first sample using the Peng-Robinson equation of state with the multi-component approach are 2.6 and 10.2 and 7.4, respectively, and for the PC-SAFT equation of state with the multi-component approach are 2.3, 8.9 and 6.6, respectively; For the second example, using the Peng-Robinson equation with a multi-component approach, 2.3, 7.3 and 1.5, respectively, and for the PC-SAFT equation, the multi-component is 1.8, 3.9 and 1.5, respectively. In general, it can be said that the PC-SAFT equation is superior to the Peng-Robinson equation, and the multi-component model improves performance.
