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Experimental Study and Model Optimization of Carbon Dioxide Dissolved Gas Crude Oil
HE Yanan, XIONG Xiaoqin, HUANG Delin, WANG Peiyao, MA Qizhao, LIAO Tao
Xinjiang Oil & Gas
2026, 22 (1):
133-142.
DOI: 10.12388/j.issn.1673-2677.2026.01.015
With the technical progress in carbon dioxide (CO
2) flooding for enhanced oil recovery (CO
2-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 CO
2
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.
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