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Study on reaction equations of heavy oil aquathermolysis with superheated steam

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Abstract

Aquathermolysis is an important approach to in situ conversion, a form of heavy oil thermal recovery technology. The aquathermolysis reaction models for high-sulfur heavy oil previously proposed by scholars are not suitable for low-sulfur heavy oil. Additionally, the essence of an aquathermolysis reaction is the change in the heavy oil composition, which cannot be characterized by existing models. To address these two problems, we established an aquathermolysis model for low-sulfur heavy oil, which can characterize the composition change. This model is based on material balance, reaction kinetics, and the Arrhenius equation and includes the aquathermolysis equation, the reaction kinetics model, and the Gaussian reaction rate model. We compared results of the modified model with an experimental model and found the following: (1) The characteristics of aquathermolysis of low-sulfur heavy oil were in accordance with its Gaussian type, (2) the model could predict the composition change of heavy oil more accurately and could more precisely predict the gas reaction rate of low-sulfur heavy oil, and (3) the model has a common applicability for low-sulfur heavy oil of different viscosities.

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Acknowledgements

The authors acknowledge the support of the National Science and Technology Major Project (Nos. 2016ZX05025-004-002 and 2016ZX05012-005-004) and the National Natural Science Fund of China (No. U1762102).

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Authors and Affiliations

  1. College of Petroleum Engineering, China University of Petroleum (Beijing), Beijing, 102249, People’s Republic of China

    S. Huang, M. Cao, Q. Huang, B. Liu & J. Jiang

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  1. S. Huang
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  2. M. Cao
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  3. Q. Huang
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  4. B. Liu
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  5. J. Jiang
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Correspondence to M. Cao.

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All the authors declare that they have no conflicts of interest.

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Editorial responsibility: iskender AKKURT.

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Huang, S., Cao, M., Huang, Q. et al. Study on reaction equations of heavy oil aquathermolysis with superheated steam. Int. J. Environ. Sci. Technol. 16, 5023–5032 (2019). https://doi.org/10.1007/s13762-018-1799-3

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  • DOI: https://doi.org/10.1007/s13762-018-1799-3

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