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A semi-compositional approach to model asphaltene precipitation and deposition in solvent-based bitumen recovery processes

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Listed:
  • Chai, Maojie
  • Nourozieh, Hossein
  • Chen, Zhangxin
  • Yang, Min

Abstract

Steam assisted gravity drainage (SAGD), as a commercially proven high ultimate recovery process for heavy oil and bitumen is energy intensive and may be limited by high usage of water. In the recent years, numerous methods to combine solvent and heat have been proposed for the in-situ recovery of bitumen. Among these methods, N-Solv (heated solvent vapor injection) and EBRT (enhanced bitumen recovery technology) utilize heated solvent vapor to extract heavy crudes under in situ conditions. These methods take the advantage of partial in situ upgrading of oil with much lower consumptions of water and natural gas and have the potential to reduce greenhouse gas (GHG) emissions. However, with the current knowledge relevant to solvent/heat-assisted recovery processes, it still remained uncertain how the in-situ upgrading could impact ultimate recovery and the efficiency of these processes. This study, thus, aims at providing insights about these processes with a numerical model. The study develops a simulation model that captures important mechanisms involved in the processes such as diffusion/dispersion, solvent dissolution, asphaltene precipitation and potential deposition. The complexity of modelling such processes is due to interrelation of oil–gas phase behavior and fluid transport mechanisms combined with in situ upgrading of oil. The intention is not to only identify factors important to the modeling of these processes, but also find how robust simulation models can be developed to replicate observed field behavior. A semi-compositional approach, based on liquid–liquid equilibrium, is proposed to properly capture the asphaltene precipitation in thermal numerical simulators using direct lab measured data. Our analysis will be presented regarding upgrading mechanisms that should be implemented, their effect on the oil production rate, and techniques to model them.

Suggested Citation

  • Chai, Maojie & Nourozieh, Hossein & Chen, Zhangxin & Yang, Min, 2022. "A semi-compositional approach to model asphaltene precipitation and deposition in solvent-based bitumen recovery processes," Applied Energy, Elsevier, vol. 328(C).
  • Handle: RePEc:eee:appene:v:328:y:2022:i:c:s0306261922014544
    DOI: 10.1016/j.apenergy.2022.120197
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    References listed on IDEAS

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    1. Mohammad S. Masnadi & Giacomo Benini & Hassan M. El-Houjeiri & Alice Milivinti & James E. Anderson & Timothy J. Wallington & Robert Kleine & Valerio Dotti & Patrick Jochem & Adam R. Brandt, 2021. "Carbon implications of marginal oils from market-derived demand shocks," Nature, Nature, vol. 599(7883), pages 80-84, November.
    2. Hashemi, Rohallah & Nassar, Nashaat N. & Pereira Almao, Pedro, 2014. "Nanoparticle technology for heavy oil in-situ upgrading and recovery enhancement: Opportunities and challenges," Applied Energy, Elsevier, vol. 133(C), pages 374-387.
    3. Dong, Xiaohu & Liu, Huiqing & Chen, Zhangxin & Wu, Keliu & Lu, Ning & Zhang, Qichen, 2019. "Enhanced oil recovery techniques for heavy oil and oilsands reservoirs after steam injection," Applied Energy, Elsevier, vol. 239(C), pages 1190-1211.
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    1. Chai, Maojie & Chen, Zhangxin & Nourozieh, Hossein & Yang, Min, 2023. "Numerical simulation of large-scale seasonal hydrogen storage in an anticline aquifer: A case study capturing hydrogen interactions and cushion gas injection," Applied Energy, Elsevier, vol. 334(C).

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