Usage
  • 189 views
  • 242 downloads

Multiphase Equilibria and Miscibility of Reservoir Fluids in Tight/Shale Reservoirs

  • Author / Creator
    Sun, Hao
  • The phase behavior of reservoir fluids in tight/shale reservoirs can be dramatically altered from the bulk phase behavior due to the strong capillarity and confinement effects introduced by the confined nanopores found in the unconventional reservoirs. Therefore, an accurate description of the phase behavior of reservoir fluids in unconventional reservoirs cannot be obtained from the conventional multiphase equilibrium calculation algorithm when a high capillary pressure is present in nanopores. Moreover, due to the shift of reservoir fluids’ phase behavior in nanopores, the miscibility between the reservoir fluids and the injection gas becomes different from that in the bulk conditions. Consequently, the compositional reservoir simulation that uses the conventional phase behavior calculation model will result in unreliable outputs when it is used to simulate tight/shale reservoirs. Therefore, calculation algorithms that can capture the effects of capillarity and confinement on the multiphase equilibrium and oil-gas minimum miscibility pressure (MMP) in nanopores are needed.
    This thesis aims to minimize the difference between the multiphase equilibrium calculation results and the results obtained from experiments. The thesis first employs a modified Young-Laplace equation proposed by Tan and Piri (2015) and couples it with the Peng-Robinson equation of state (PR-EOS) model (Peng and Robinson, 1976). Then, the experimental data of phase transitions in confined nanopores are collected from literature to develop the λ correlations in the modified Young-Laplace equation for pure hydrocarbons and mixtures. The phase behavior results calculated using the proposed algorithm are validated by the experimental data.
    Efforts are also made to develop a robust and comprehensive three-phase equilibrium calculation algorithm package that can reliably predict the three-phase equilibria of reservoir fluids in nanopores with two capillary pressures. The two capillary pressures refer to the capillary pressure between the gas phase and the oleic phase as well as the capillary pressure between the oleic phase and the aqueous phase. The new three-phase equilibrium calculation algorithm is capable of predicting the aqueous-oleic-vapor three-phase boundary for a given mixture in nanopores. The results show that the aqueous-oleic-vapor three-phase envelope in confined nanopores appears to be different from the one in bulk conditions. This is the first modeling study investigating how two capillary pressures affect the aqueous-oleic-vapor three-phase equilibria in nanopores.
    Another task of this thesis is to improve the prediction of MMP of crude oil being displaced by carbon dioxide (CO2) in nanopores by coupling the capillarity and confinement effect into the modified Multiple-Mixing-Cell (MMC) method (Ahmadi and Johns, 2011). A state-of-art volume translation model is used in the PR-EOS model for a better prediction of phase densities. This work also proposes a simple MMP calculation strategy that considers the pore size distribution of tight/shale cores. Using the developed MMC code, we investigate how nanopore size, pore size distribution, and temperature influence the MMP between CO2 and crude oil.
    The last work of this thesis is to develop a modified cell-to-cell method that can be used to simultaneously calculate MMP and oil recovery factors during the gas flooding process in a confined space. In this work, the original cell-to-cell method proposed by Metcalf et al. (1973) is coupled with the capillary-pressure model and the critical point shift model (Tan et al., 2019). The advantage of this cell-to-cell simulation model (Metcalfe et al., 1973) over the MMC method developed by Ahmadi and Johns (2011) is that the cell-to-cell model mimics the physical 1-D gas displacement process. MMP as well as the final oil recovery factor can be obtained through the modified cell-to-cell calculation algorithm.

  • Subjects / Keywords
  • Graduation date
    Spring 2021
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/r3-jxs4-f983
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.