新疆石油天然气 ›› 2026, Vol. 22 ›› Issue (1): 133-142.DOI: 10.12388/j.issn.1673-2677.2026.01.015

• 新能源 • 上一篇    

二氧化碳溶气原油黏度实验研究及模型优化

贺雅楠1，熊小琴1，黄德林1，王培尧1，马启钊2，廖涛2

  1. 1.中国石油大学（北京）克拉玛依校区，新疆克拉玛依  834000；2.中国石油新疆油田分公司采油工艺研究院，新疆克拉玛依  834000

  • 收稿日期:2025-11-16 修回日期:2026-01-12 接受日期:2026-01-13 出版日期:2026-03-10 发布日期:2026-03-10
  • 通讯作者: 熊小琴（1983-），2007年毕业于西南石油大学油气储运专业，硕士，副教授，主要从事油气输送工艺优化方面的研究和教学工作。（E-mail）xiongxiaoqin@cupk.edu.cn
  • 作者简介:贺雅楠（2002-），中国石油大学（北京）油气储运专业在读硕士研究生，主要研究方向为油气储运工艺优化。（E-mail）heyananm@163.com
  • 基金资助:
    新型油气勘探开发国家科技重大专项“准噶尔盆地砾岩油藏CCUS-EOR混相驱技术与集成示范”（2025ZD1408400）。

Experimental Study and Model Optimization of Carbon Dioxide Dissolved Gas Crude Oil

HE Yanan1，XIONG Xiaoqin1，HUANG Delin1，WANG Peiyao1，MA Qizhao2，LIAO Tao2   

  1. 1.Karamay Campus，China University of Petroleum （Beijing），Karamay 834000，Xinjiang，China；2. Oil Production Technology Research Institute，PetroChina Xinjiang Oilfield Company，Karamay 834000，Xinjiang，China

  • Received:2025-11-16 Revised:2026-01-12 Accepted:2026-01-13 Online:2026-03-10 Published:2026-03-10

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摘要： 随着CO2驱油提高采收率（CO2-EOR）技术的发展，研究CO₂注入对原油黏度的影响机制具有重要意义。通过室内实验系统考察了温度（20~40 ℃）、压力（0.5~3.5 MPa）和含水率（0%~60%）对饱和CO₂溶气原油黏度的协同影响。结果表明：在恒定压力下，温度每升高5 ℃，黏度下降约60%~80%；在恒定温度下，压力每增加0.5 MPa，黏度下降约1%~5%；反相点前（含水率<40%），含水率每增加10%，黏度上升15%~50%；反相点后（含水率>40%），含水率每增加10%，黏度下降50%~80%。基于实验数据，评估了Standing、Glaso和Vazquez & Beggs（V&B）三种经典模型的预测性能，发现V&B模型具有最优的鲁棒性。采用XGBoost算法结合贝叶斯优化对V&B模型进行动态修正，建立了温度-压力-含水率的多参数映射关系，将模型平均相对误差从20.1%降低至6.9%，平均绝对误差降低约66%。研究成果可为CO₂驱油条件下油气集输系统的工艺设计与动态优化提供理论依据和智能预测工具。

关键词: CO2溶气原油, 黏度模型, XGBoost, 贝叶斯优化, 降黏机理

Abstract: With the technical progress in carbon dioxide （CO2） flooding for enhanced oil recovery （CO2-EOR），it is of great significance to study the influence mechanism of CO₂ injection on the viscosity of crude oil. This study systematically investigated the synergistic effects of temperature （20-40 ℃），pressure （0.5-3.5 MPa），and water content （0%-60%） on the viscosity of saturated CO2  dissolved gas crude oil through laboratory experiments. The results showed that under constant pressure，for every 5℃ increase in temperature，the viscosity decreases by approximately 60%-80%. At a constant temperature，for every 0.5 MPa increase in pressure，the viscosity decreases by approximately 1%-5%. In terms of water content，a 10% increase in water content leads to a rise in viscosity by 15%-50% before the inverted point （water content < 40%）. After the inverted point （water content>40%），for every 10% increase in water content，the viscosity decreases by 50%-80%. Based on the experimental data，the prediction performance of three classic models，namely Standing，Glaso and Vazquez & Beggs （V&B），was evaluated. It was found that the V&B model had the best robustness. The XGBoost algorithm combined with Bayesian optimization was used to dynamically correct the V&B model，and a multi-parameter mapping relationship of temperature，pressure and water content was established. The average relative error of the model was reduced from 20.1% to 6.9%，and the average absolute error was decreased by approximately 66%. This study provides a theoretical basis and intelligent prediction tool for the process design and dynamic optimization of oil and gas gathering and transportation systems under CO₂ flooding conditions.

Key words: CO2 , dissolved gas crude oil；viscosity model；XGBoost；Bayesian optimization；viscosity reduction mechanism

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