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Modelling the rheology of complex fluids : Cases of bitumen and heavy oils at low temperatures.

机译:模拟复杂流体的流变性:低温下沥青和重油的情况。

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摘要

As complex fluids such as heavy oil or bitumen pass from the field to process units, structural and compositional changes occur that are intimately linked with pressure (P), temperature (T), and shear histories. In this exploratory work, a modified Structural Kinetics Model is used to calculate the apparent shear viscosity of three complex fluids: Maya Crude Oil (MCO), Athabasca Bitumen (AB) and Safaniya Heavy Oil (SP) and their related nano-filtered fractions (permeates and retentates) at low temperatures. The proposed model involves a structural parameter λ that tracks the mechanical history of these fluids and a temperature shift factor aTP that integrates the thermal history, through the usage of the concept of fictive temperature T eff inside a modified Williams Landel Ferry (WLF) equation. Rheological data for the feedstocks were divided into a training data set, used to fit model parameters, and an extrapolation data set, used to test the asymptotic behaviour of the model with respect to temperature and shear history. Rheological data for the nano-filtered permeates and retentates, with varying mass fractions of structured phase, comprised a prediction data set. Average absolute deviations (AAD) less than 15% and R2 values approaching unity were obtained for the prediction data set. AAD values were less than 4 % for the training and less than 10 % for the extrapolation data sets. The modified Structure-Kinetics Model offers insights, as well as flexibility and accuracy for simulating heavy oil and bitumen rheological properties under conditions where these fluids are structured.
机译:随着复杂流体(例如重油或沥青)从田间流向工艺单元,结构和组成的变化会发生,与压力(P),温度(T)和剪切历史密切相关。在这项探索性工作中,使用改良的结构动力学模型来计算三种复杂流体的表观剪切粘度:玛雅原油(MCO),阿萨巴斯卡沥青(AB)和萨法尼亚重油(SP)及其相关的纳滤级分(渗透和截留)。拟议的模型涉及一个结构参数λ,该参数跟踪流体的机械历史,而温度变化因子aTP则通过在改进的Williams Landel Ferry(WLF)方程中使用虚拟温度T eff的概念来积分热历史。原料的流变数据分为训练数据集(用于拟合模型参数)和外推数据集(用于测试模型相对于温度和剪切历史的渐近行为)。纳米过滤的渗透物和截留物的流变学数据具有不同的结构相质量分数,包括一个预测数据集。对于预测数据集,获得的平均绝对偏差(AAD)小于15%,R2值接近于1。训练的AAD值小于4%,外推数据集的AAD值小于10%。修改后的“结构动力学模型”提供了洞察力,以及在构造这些流体的条件下模拟重油和沥青流变特性的灵活性和准确性。

著录项

  • 作者

    Dion, Moise.;

  • 作者单位

    University of Alberta (Canada).;

  • 授予单位 University of Alberta (Canada).;
  • 学科 Engineering Electronics and Electrical.;Engineering Petroleum.
  • 学位 M.S.
  • 年度 2011
  • 页码 174 p.
  • 总页数 174
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 老年病学;
  • 关键词

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