纳米二氧化硅（nano-SiO₂）注入储层后可有效避免CO₂对储层岩石的酸蚀，保障CO₂封存安全性。目前研究中无法实现nano-SiO₂-CO₂ （nano-SiO₂协同CO₂混和流体）注入井温度分布准确预测，导致nano-SiO₂-CO₂注入后难以精确控制地层温度，影响封存的安全性。基于质量守恒、能量守恒，建立考虑气-液-固比例分布的nano-SiO₂-CO₂注入井温度分布预测模型，并通过nano-SiO₂-CO₂注入管道摩阻实验，提出超临界状态下不同流态nano-SiO₂-CO₂混合流体井筒摩擦系数计算模型，实现了nano-SiO₂-CO₂注入井温度分布准确预测。现场井温度分布计算结果表明：温度预测误差小于1%，验证了模型的可靠性。最后通过nano-SiO₂-CO₂注入井温度数值模拟分析，明确不同参数对nano-SiO₂-CO₂注入井温度分布的影响规律，为nano-SiO₂-CO₂注入参数优化提供理论支撑，进而提高nano-SiO₂-CO₂注入效果、确保CO₂封存安全性。

After the injection of nano-silica (nano-SiO₂) into the reservoir, the acid corrosion of CO₂ on reservoir rocks can be effectively avoided, ensuring the safety of CO₂ storage. However, accurate prediction of the temperature distribution in nano-SiO₂-CO₂(nano-SiO₂ synergistic CO₂ mixed fluid) injection wells is currently not achievable in existing research, which makes it difficult to precisely control the formation temperature after nano-SiO₂-CO₂ injection, thereby impacting the safety of storage. A temperature distribution prediction model for nano-SiO₂-CO₂ injection wells, considering the gas-liquid-solid ratio distribution, was established based on mass conservation and energy conservation principles. Furthermore, through the nano-SiO₂-CO₂ injection pipeline friction experiment, a model for calculating the wellbore friction factor of nano-SiO₂-CO₂ mixed fluids under supercritical conditions and different flow regimes was proposed. This model enabled accurate prediction of the temperature distribution in nano-SiO₂-CO₂ injection wells. The field well temperature distribution calculation results show that the temperature prediction error is less than 1%, verifying the reliability of the model. Finally, through numerical simulation analysis of nano-SiO₂-CO₂ injection well temperatures, the impact laws of various parameters on the temperature distribution were clarified, providing theoretical support for optimizing nano-SiO₂-CO₂ injection parameters, thereby improving the injection efficiency and ensuring the safety of CO₂ storage.