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Abstract The waxy crude oil exhibits a time- and shear-dependent non-Newtonian behavior called thixotropic behavior below the gelation temperature. This behavior can be quantitatively described by using a thixotropic model. However, many parameters are commonly contained in a thixotropic model with good-description capacity, and it still remains challenging to obtain high fitting precision and reasonable physical interpretation simultaneously in the process of parametric regression. In this study, based on a representative multiparameter thixotropic model, a multiobjective regression strategy is put forward. The fitting precision and physical interpretation are taken into account in this regression strategy, and their importance can be adjusted dynamically with the structure breakdown of waxy crude oil. In order to successfully achieve the multiobjective regression strategy, a self-adaptive nondominated sorting differential evolution algorithm (self-adaptive NSDE) is proposed. This regression algorithm is independent on the expressions of the regression model, and thus it can also be applied to the multiobjective parametric regression of other complex models including thixotropic models in rheology field and even other models in different fields. Based on experimental data, the parametric regression of a thixotropic model is performed, and the obtained results are analyzed and discussed in detail. It is found that the regressive data exhibit a small deviation at the starting stage of structure breakdown and the equilibrium flow curve can be ensured at the ending stage of structure breakdown. This finding well verifies considerations of multiobjective regression strategy. Compared with previous three regression strategies in the literature reports, the multiobjective regression strategy exhibits advantages in the fitting precision and physical interpretation. Highlights • A novel multiobjective regression strategy for the parametric regression of thixotropic model is established. • A multiobjective regression algorithm named self-adaptive NSDE is proposed. • The influences of equilibrium flow curve and static yield stress on the deviation of regressive results are obtained. • Multiobjective regression strategy is verified to be better than the previous three regression strategies. [ABSTRACT FROM AUTHOR]

When several kinds of crude oil need to be transported, the batch pipelining is a better choice than the “single-pipeline-single-oil” and blending pipelining due to its advantages. In the batch pipelining process, to avoid the frequent operations on the pumps and control valves, the flow rate is generally inconstant in practice. All previous studies simplify the flow rate distribution as a constant one, which largely deviates from the engineering practice. Focused on this point, based on the features of the batch pipelining in practice, the gradient-type flow rate distribution model and corresponding calculation approach are proposed in this paper. The accuracy of this model and corresponding calculation approach are verified by the field data, and it indicates that the accuracy of numerical results can meet the engineering requirement. Further, the thermal characteristics of the batch pipelining are found by numerical simulation and the further analysis is carried out to make these characteristics more convincing. Finally, the shortcoming of the step-type flow rate distribution with simple expression is pointed out. It is found that the adoption of the step-type flow rate distribution in the simulation would introduce a prominent deviation when the change period of flow rate is relatively long. To overcome this shortcoming, the proposed gradient-type flow rate distribution, whose accuracy is higher, is an alternative method. [ABSTRACT FROM AUTHOR]

With the depleting of conventional oil and gas resources, viscosity reduction of heavy oil became more and more important as a research focus. As a new method of viscosity reduction, the mechanism of microwave-assisted with nano-catalysts is still unclear. In this paper, the viscosity reduction of nano-catalyst and microwave treatment of heavy oil in different water content was studied. The experimental results showed that the maximum viscosity reduction was 96.81 % when the water content was 50 wt% under the conditions of microwave heating power of 614w, microwave heating temperature of 68 °C and nickel nano-catalyst concentration of 0.8 wt%. The oil samples before and after three treatments were analyzed by infrared spectroscopy, element analysis, four-component separation, and two-dimensional gas chromatography-mass spectrometry. By analyzing the changes of functional group, element composition, and component content, the effects of microwave and nano-catalyst were studied. The results showed that the resin and asphaltene content decreased by 17.3 wt%, and the hydrogen to carbon ratio was 2.14 when the water content was 30 wt% under the conditions of microwave heating power of 666w, microwave heating temperature of 65 °C and nickel nano-catalyst concentration of 2.3 wt%, which proved that microwave treatment assisted with nano-catalysts could increase the cracking capacity of macromolecules and the production of coke. • Resin and asphaltene content decreased by 17.3 wt% when water content was 30 wt% under synergistic effect of microwave and nano-catalyst. • Hydrogen to carbon ratio was 2.14 when water content was 30 wt% under synergistic effect of microwave and nano-catalyst. • Above results proved that microwave treatment assisted with nano-catalysts could increase the cracking capacity of macromolecules. • In synergistic effect of microwave and nano-catalyst, bicyclic aromatic hydrocarbons decreased to 13.40 %. • In synergistic effect, tricyclic aromatic hydrocarbons increased to 11.53 %, and hopanidanes increased from 1.50 % to 1.63 %. [ABSTRACT FROM AUTHOR]