Abstract Thermal conductivity data for crude (mainly heavy) oils and mixtures of crude oils and pure hydrocarbons were collected at temperatures from 20 to 125 °C and pressures up to 10 MPa using a hot wire apparatus. A criterion was established to screen out data that were affected by convection. The screened data and data from the literature were used to develop an Expanded Fluid (EF) based thermal conductivity model for pure hydrocarbons, crude oils and their mixtures. The proposed model is applicable across the entire phase diagram including the critical region; however, it does not predict the critical enhancement of thermal conductivity observed in the vicinity of the critical point. The model inputs are the density of the fluid, the pressure, the dilute gas thermal conductivity, the compressed state density, and three other fluid specific parameters. The gas thermal conductivity is calculated from a well-established correlation. The compressed state density is obtained from the literature or from fitting the EF viscosity model to viscosity data. The three fluid specific parameters are determined by fitting the model to thermal conductivity data. The model fits the data of 63 pure hydrocarbons at temperatures from −150 to 330 °C and pressures up to 200 MPa with average deviation of 4%, except in the vicinity of the critical point (0.97

中文翻译：

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扩展的基于流体的碳氢化合物和原油热导率模型

摘要 使用热线装置在 20 至 125 °C 的温度和高达 10 MPa 的压力下收集原油（主要是重油）以及原油与纯烃的混合物的热导率数据。建立了一个标准来筛选出受对流影响的数据。筛选数据和文献中的数据用于开发基于膨胀流体 (EF) 的纯碳氢化合物、原油及其混合物的热导率模型。所提出的模型适用于包括临界区在内的整个相图；然而，它并没有预测在临界点附近观察到的热导率的临界增强。模型输入是流体密度、压力、稀释气体热导率、压缩状态密度、和其他三个流体特定参数。气体热导率是根据公认的相关性计算的。压缩状态密度是从文献中获得的，也可以从将 EF 粘度模型拟合到粘度数据中获得。通过将模型拟合到热导率数据来确定三个流体特定参数。该模型拟合了 63 种纯碳氢化合物在 -150 至 330 °C 和高达 200 MPa 压力下的数据，平均偏差为 4%，临界点附近（0.97