Viscosity-temperature characteristics and prediction models for highly asphaltic heavy oils

SHEN Hao; TANG Xuemei; ZHANG Yueyue; ZHANG Yanan; LIN Xufeng; YANG Junwei

doi:10.11949/0438-1157.20260730

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Viscosity-temperature characteristics and prediction models for highly asphaltic heavy oils

更新时间：2026-08-24

- Viscosity-temperature characteristics and prediction models for highly asphaltic heavy oils
- CIESC Journal (2026)
- 作者机构：
  
  中国石油大学（华东）重质油全国重点实验室，山东青岛 266580
- 作者简介：
- 基金信息：
- DOI：10.11949/0438-1157.20260730
  CLC： TE 621
- Received：29 May 2026，
  
  Revised：2026-08-22，
  
  Accepted：24 August 2026，
- 稿件说明：
移动端阅览
SHEN Hao, TANG Xuemei, ZHANG Yueyue, et al. Viscosity-temperature characteristics and prediction models for highly asphaltic heavy oils[J/OL]. CIESC Journal, 2026.
DOI：

SHEN Hao, TANG Xuemei, ZHANG Yueyue, et al. Viscosity-temperature characteristics and prediction models for highly asphaltic heavy oils[J/OL]. CIESC Journal, 2026. DOI： 10.11949/0438-1157.20260730.

摘要

高沥青质重油是复杂的胶体体系，黏度是其重要的基础物性，然而现有黏度预测模型对高沥青质重油的适用性欠佳或计算过程复杂。本研究以脱油沥青和减压渣油为原料，调和成不同沥青质含量的混合油品，在120~210℃区间内测定黏温曲线，并结合分子动力学模拟，研究组分相互作用、扩散和聚集行为与重油黏度的内在关系。结果表明，高沥青质重油黏度的影响机制表现为组分间相互作用及扩散行为的微观调控。采用五种混合黏度预测模型预测了混合油品黏度，对比结果表明，双对数模型与Arrhenius模型预测精度最优，平均相对偏差分别为8.71%和9.54%，而Cragoe模型预测偏差高达56.62%。建立了基于软化点的黏温曲线预测模型，采用软化点指标可完成高沥青质重油黏度曲线的准确预测，平均相对偏差约为10%，具有计算简便、输入参数易测、满足工程计算精度要求的优势。

Abstract

High-asphaltene heavy oil is a complex colloidal system

and viscosity serves as one of its key fundamental physical properties. However

existing viscosity prediction models show poor applicability to high-asphaltene heavy oil or require cumbersome calculations. In this study

deoiled asphalt and vacuum residue were blended to prepare mixed oil samples with different asphaltene contents

and their viscosity-temperature curves were measured at temperatures ranging from 120 to 210 °C. Combined with molecular dynamics simulations

the intrinsic relationships between viscosity of heavy oil and the component interactions

diffusion

and aggregation behaviors of components were explored. The results demonstrate that the viscosity of high-asphaltene heavy oil is microscopically regulated by inter-component interactions and diffusion behaviors. Five composite viscosity prediction models were used for prediction

and the comparison results show that the double logarithmic model and Arrhenius model achieve the best prediction accuracy with average relative deviations of 8.71% and 9.54%

respectively

while the Cragoe model presents a considerably high deviation of 56.62%. A viscosity-temperature curve prediction model based on softening point was further established

which can accurately predict the viscosity curves of high-asphaltene heavy oil with an average relative deviation of around 10%. This model boasts simple calculation

easily measurable input parameters and favorable accuracy that meets the requirements of engineering calculations.

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references

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