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Modern Bitumen Oil Mixture Models in Ashalchinsky Field with Low-Viscosity Solvent at Various Temperatures and Solvent Concentrations

Author

Listed:
  • Gulnur Zakirova

    (Department of Transport and Storage of Oil and Gas, Saint Petersburg Mining University, 199106 Saint Petersburg, Russia)

  • Vladimir Pshenin

    (Department of Transport and Storage of Oil and Gas, Saint Petersburg Mining University, 199106 Saint Petersburg, Russia)

  • Radmir Tashbulatov

    (Department of Transport and Storage of Oil and Gas, Ufa State Petroleum Technological University, 450064 Ufa, Russia)

  • Lyubov Rozanova

    (Department of Transport and Storage of Oil and Gas, Saint Petersburg Mining University, 199106 Saint Petersburg, Russia)

Abstract

The article analyzes the modern theory and practice of pipeline transport of bituminous oil together with low-viscosity solvent. In addition, a detailed analysis of the rheological models of non-Newtonian fluids is carried out, which establishes a number of assumptions on the rheology model selection algorithm currently in use (limited number of rheological models, variability in model coefficient assignment, etc.). Ways of their elimination are proposed. Dependencies for determination of the dynamic viscosity coefficient of binary oil mixtures are investigated. Calculation of the parameters of the bituminous oil mixture with solvent is considered. Complex experimental studies on rheology mixture models of bituminous oil and solvent on the example of the Ashalchinsky field (Russia, Tatarstan) in a wide range of temperatures and concentrations of the solvent are conducted. A two-dimensional field of rheological models of the oil mixture is constructed, which makes it possible to determine the rheological model of the pumped oil mixture depending on the solvent concentration and the temperature of the mixture. Formulas for forecasting the rheological properties of the oil mixture on the basis of statistical processing of the results of experimental studies are theoretically substantiated. It is proven that the viscosity of binary oil mixtures in the Newtonian fluid field should be determined by a modified Arrhenius equation. The proposed models with a high degree of accuracy describe the rheological properties of the oil mixture. It is shown that in the case of complex mixtures, not one rheological model should be applied, but their hierarchy should be established depending on the solvent concentration and temperature.

Suggested Citation

  • Gulnur Zakirova & Vladimir Pshenin & Radmir Tashbulatov & Lyubov Rozanova, 2022. "Modern Bitumen Oil Mixture Models in Ashalchinsky Field with Low-Viscosity Solvent at Various Temperatures and Solvent Concentrations," Energies, MDPI, vol. 16(1), pages 1-18, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:395-:d:1019097
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    References listed on IDEAS

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    1. Ekaterina Leusheva & Valentin Morenov, 2022. "Effect of Temperature Conditions in Arctic Offshore Oil Fields on the Rheological Properties of Various Based Drilling Muds," Energies, MDPI, vol. 15(15), pages 1-10, August.
    2. Inzir Raupov & Ramis Burkhanov & Azat Lutfullin & Alexander Maksyutin & Andrey Lebedev & Elena Safiullina, 2022. "Experience in the Application of Hydrocarbon Optical Studies in Oil Field Development," Energies, MDPI, vol. 15(10), pages 1-18, May.
    3. Anatoliy Andreevich Isaev & Mekhrali Mirzali Ogly Aliev & Alexander Nikolaevich Drozdov & Yana Alekseevna Gorbyleva & Karina Shamilyevna Nurgalieva, 2022. "Improving the Efficiency of Curved Wells’ Operation by Means of Progressive Cavity Pumps," Energies, MDPI, vol. 15(12), pages 1-14, June.
    4. Pouya Abdollahpour & Seyyed Shahab Tabatabaee Moradi & Ekaterina Leusheva & Valentin Morenov, 2022. "A Numerical Study on the Application of Stress Cage Technology," Energies, MDPI, vol. 15(15), pages 1-13, July.
    5. Ke Wang & Harrie Vredenburg & Jianliang Wang & Yi Xiong & Lianyong Feng, 2017. "Energy Return on Investment of Canadian Oil Sands Extraction from 2009 to 2015," Energies, MDPI, vol. 10(5), pages 1-13, May.
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    Cited by:

    1. Andrey Lebedev & Alexey Cherepovitsyn, 2024. "Waste Management during the Production Drilling Stage in the Oil and Gas Sector: A Feasibility Study," Resources, MDPI, vol. 13(2), pages 1-30, February.

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