1887

Abstract

Summary

Benchmarking the Ultimate Recovery of a field with producing reservoir analogues is required in the industry to support and increase confidence in the resources evaluation. This paper presents a novel method to mitigate or deactivate miscibility effects in coarse 3D miscible gas compositional simulations. The proposed straightforward method allows the enrichment of an analogue database by including oil fields exhibiting either a lower degree of miscibility or in immiscible conditions.

When pressure increases, the gas-oil interaction becomes so strong that gas/oil relative permeabilities (G/O KRs) have minimal impact. As a consequence, the impact of miscibility is often overestimated in coarse grid simulations.

This is partly due to the assumption of instantaneous G/O equilibrium and also uniform composition in the grid block. Black oil simulation allows to slow down the G/O interaction easily, but similar keywords are not present in commercial compositional simulators, making such a correction much more challenging. But in miscible flooding compositional simulation, the strength of gas-oil interaction is such that this correction is more needed, but also more difficult to perform than in immiscible simulation. Some existing methods are listed, with their drawbacks and limitations.

This current methodology works on the Binary Interaction Coefficients, progressively hindering the gas-oil interaction when they are increased, and thus degrading the miscibility behavior.

This work allows to degrade the miscibility not only of pure gases, like published before, but also of gases with complex composition. It also allows to keep a 3D trend in the original oil composition, as frequently needed on fields with an initial compositional gradient The method was tested over a deep offshore green field, planned to be developed with total gas reinjection using a WAG injection scheme. The method allowed to compare resources for miscible gas with immiscible gas injections, quantifiying the miscibility impact on recovery, providing confidence in the evaluations. It works both for continuous and alternate injections, allowing to benchmarck miscible WAG with near-miscible WAG and immiscible WAG.

This method is allowing a progressive correction, thus allowing it to be used for upscaling, depending on grid size: no correction on very fine grid, a minor correction on fine grid, and a strong correction on coarse grid.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202531054
2025-04-02
2026-02-06
Loading full text...

Full text loading...

References

  1. Al-Haboobi, Z.I.M., Christie, M.A. and Graham, A.J.: “Calibrating the Todd and Longstaff Mixing Parameter Value for Miscible Finite-Sized Slug WAG Injection for Application on a Field Scale”, SPE-185858, 2020.
    [Google Scholar]
  2. Al-Wahaibi, Y., Muggeridge, A. H., and Grattoni, C.A.: 'Experimental and numerical studies of gas/oil multicontact miscible displacements in homogeneous porous media’, SPE 92887, 2005.
    [Google Scholar]
  3. Barker, J.W and Fayers, F.J.: “Transport Coefficients for Compositional Simulation with Coarse Grids in Heterogeneous Media”, SPE-22591, 1994.
    [Google Scholar]
  4. Barker, J., Prevost, M. and Pitrat, E.:“Simulating Residual Oil Saturation in Miscible Gas Flooding Using Alpha-Factors”, SPE-93333, 2004.
    [Google Scholar]
  5. Bourgeois, M.J., Gommard, D.R. and Gouas, H.“Simulating Early Gas Breakthrough in Undersaturated Oil Using Alpha-Factors”, SPE-161460, 2012.
    [Google Scholar]
  6. Bourgeois, M.J., Boot, N., Saint-Felix, M., Boudimbou; I. and Tollis, A.: “Immiscible Gas Injection Pilot on an Offshore Mature Field with Undersaturated Viscous Oil”, SPE-190356, 2018.
    [Google Scholar]
  7. BourgeoisM.J. et al: “Miscible WAG Efficiency Assessment On A Large Mature Carbonate Field”, SPE-207384, 2021.
    [Google Scholar]
  8. Caetano Chang, P.L.K., Skauge, A., Sorbie, K.S., Rios, V. and Kumar, K.: “Modeling of Viscous Instability in Compositional Gas and WAG Injections”, EAGEIOR+, 2023.
    [Google Scholar]
  9. Coats, K. H.: “An Equation of State Compositional Model”, SPE-8284, 1980
    [Google Scholar]
  10. Coats, K.H., Whitson, C.H. and Thomas, L.K.: “Modeling Conformance as Dispersion”, SPE-90390, SPERE2009
    [Google Scholar]
  11. Fayers, F.J., Blunt, M.J. and Christie, M.A.: “Comparison of Empirical Viscous-Fingering Models and Their Calibration for Heterogeneous Problems, SPE-22184, 1992.
    [Google Scholar]
  12. Garmeh, G and Johns, R.T.: “Upscaling of Miscible Floods in Heterogeneous Reservoirs Considering Reservoir Mixing”, SPE-124000, 2010.
    [Google Scholar]
  13. Hoier, L., Cheng, N. and Whitson, C.H.: “Miscible Gas Injection in Undersaturated Gas-Oil Systems”, SPE-90379, 2004.
    [Google Scholar]
  14. Lantz, R.B.: “Rigorous Calculation of Miscible Displacement Using Immiscible Reservoir Simulators”, SPE-2594, 1970.
    [Google Scholar]
  15. Mogensen, K., Hood, P., Lindeloff, N., Frank., S. and Noman, R.: “Minimum Miscibility Pressure Investigation for a Gas Injection EOR Project in Al Shaheen Field, Offshore Qatar”, SPE-124109, 2009.
    [Google Scholar]
  16. Montel, F. and Quettier, L.: “Getting the Best From The Black-Oil Approach for Complex Reservoir Fluids”, SPE-90926, 2004.
    [Google Scholar]
  17. Pallotta, Q.: “Study of non-local equilibrium options in reservoir simulators” M. Sc. Thesis, NTNU -Trondheim, Norwegian University of Science and Technology, July 2013.
    [Google Scholar]
  18. Patacchini, L., Duchenne, S., Bourgeois, M., Moncorge, A. and Pallotta, Q.: «Simulation of Residual Oil Saturation on Near-Miscible Gas Flooding Through Saturation-dependant Tuning of the Equilibrium Constants”, SPE-171806, 2016.
    [Google Scholar]
  19. Pedersen, C. and Thibeau, S.: “Smorbukk Field: Fluid Modelling and Upscaling Issues to Simulate the Gas Cycling Process in Lower Tilje Formation”, SPE-83959, 2003.
    [Google Scholar]
  20. Rios, V.S., Santos, O.S., Quadros, F.B., Lykawka, R. and Schiozer, D.J.: “Methodology to Improve Miscible Gas Injection Forecast Based on a Field Scale Simulation Model”, OTC-28008, 2017.
    [Google Scholar]
  21. Rios, V.S., Santos, O.S., Quadros, F.B. and Schiozer, D.J.: “New upscaling technique for compositional reservoir simulations of miscible gas injection”, JPSE175 (2019) 389–406. https://doi.org/10.1016/j.petrol.2018.12.061
    [Google Scholar]
  22. Salehi, A. Voskov, D.V. and Tchelepi, H.A.: “Thermodynamically Consistent Transport Coefficients for Upscaling of Compositional Processes”, SPE-163576, 2013.
    [Google Scholar]
  23. Salehi, A. Voskov, D.V. and Tchelepi, H.A.: “K- Values Based Non-Equilibrium Formulation for Upscaling of Compositional Simulation, SPE-182725, 2017.
    [Google Scholar]
  24. Skauge, A., Sorbie, K.S. and van Dijke, R.„Modelling the Transition between Immiscible and Miscible WAG”, EAGEIOR2019.
    [Google Scholar]
  25. Stalkup, F.I. Jr.: “Miscible displacement” Monograph series, SPE, 1983.
    [Google Scholar]
  26. Stalkup, F.I., and Crane, S.D. (SPERE Feb. 1994). Reservoir Description Detail Required To Predict Solvent and Water Saturations at an Observation Well, SPE-22897, 1994.
    [Google Scholar]
  27. Todd, M.R. and Longstaff, W.J.: “The Development, Testing, and Application Of a Numerical Simulator for Predicting Miscible Flood Performance, SPE 3484, JPT1972.
    [Google Scholar]
  28. Wang, G, Pickup, G, Sorbie, K. Mackay, E., and Skauge, A.: “Analysis of Near-Miscible C02-WAG Displacements: The Distinction between Compositional and Interfacial Tension Effects”, SPE-193907, 2019.
    [Google Scholar]
  29. Wylie, P.L. and Mohanty, K.K.: “Effect of Wettability on Oil Recovery by Near-Miscible Gas Injection”, SPE-59476, SPERE Dec. 1996.
    [Google Scholar]
/content/papers/10.3997/2214-4609.202531054
Loading
/content/papers/10.3997/2214-4609.202531054
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error