1887

Abstract

Summary

If the aperture distribution is broad enough in a naturally fractured reservoir, even one where the fracture network is highly inter-connected, most fractures can be eliminated without significantly affecting the flow through the fracture network (Gong and Rossen, 2016). During a waterflood or enhanced-oil-recovery (EOR) process, the production of oil depends on the supply of injected water or EOR agent. This suggests that the characteristic fracture spacing for the dual-porosity/dual-permeability simulation of waterflood or EOR in a naturally fractured reservoir should account not for all fractures but only the relatively small number of fractures carrying almost all the injected water or EOR agent (“primary,” as opposed to “secondary,” fractures). In contrast, in primary production even a relatively small fracture represents an effective path for oil to flow to a production well. This distinction means that the “shape factor” in dual-permeability reservoir simulators and the repeating unit in homogenization should depend on the process involved: specifically, it should be different for primary and secondary or tertiary recovery. We test this hypothesis in a simple representation of a fractured region with a non-uniform distribution of fracture flow conductivities. We compare oil production, flow patterns in the matrix, and the pattern of oil recovery with and without the “secondary” fractures that carry only a small portion of injected fluid.

The role of secondary fractures depends on a dimensionless ratio of characteristic times for matrix and fracture flow (Peclet number), and the ratio of flow carried by the different fractures. In primary production, for a large Peclet number, treating all fractures equally is a better approximation than excluding secondary fractures; the shape factor should reflect both primary and secondary fractures. For a sufficiently small Peclet number, it is more accurate to exclude the secondary fractures. For waterflood or EOR, in most cases examined, the appropriate shape factor or repeating-unit size should reflect both primary and secondary fractures. If secondary fractures are much narrower than primary fractures, then it is more accurate to exclude them. Yet-narrower “tertiary fractures” are not always helpful for oil production, even if they are more permeable than matrix. They can behave as capillary barriers to imbibition, reducing oil recovery.

We present a new definition of Peclet number for primary and secondary production in fractured reservoirs that provides a more accurate predictor of dominant recovery mechanism in fractured reservoirs than the previously published definition.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201700352
2017-04-24
2024-04-26
Loading full text...

Full text loading...

References

  1. Saidi, A.M.
    , Reservoir engineering of fractured reservoirs (fundamental and practical aspects). 1987, Paris: Total Edition Press.
    [Google Scholar]
  2. Gilman, J.R. and H.Kazemi
    , Improved Calculations for Viscous and Gravity Displacement in Matrix Blocks in Dual-Porosity Simulators (includes associated papers 17851, 17921, 18017, 18018, 18939, 19038, 19361 and 20174). Journal of Petroleum Technology, 1988. 40(01): p. 60–70.
    [Google Scholar]
  3. Hill, A.C. and G.W.Thomas
    , A New Approach for Simulating Complex Fractured Reservoirs, in Middle East Oil Technical Conference and Exhibition. 1985, Society of Petroleum Engineers: Bahrain.
    [Google Scholar]
  4. Barenblatt, G.I., I.P.Zheltov, and I.N.Kochina
    , Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks [strata]. Journal of Applied Mathematics and Mechanics, 1960. 24(5): p. 1286–1303.
    [Google Scholar]
  5. Warren, J. and P.J.Root
    , The behavior of naturally fractured reservoirs. Society of Petroleum Engineers Journal, 1963. 3(03): p. 245–255.
    [Google Scholar]
  6. Kazemi, H., et al.
    , Numerical Simulation of Water-Oil Flow in Naturally Fractured Reservoirs. Society of Petroleum Engineers Journal, 1976. 16(06): p. 317–326.
    [Google Scholar]
  7. Kim, J.-G. and M.D.Deo
    , Finite element, discrete-fracture model for multiphase flow in porous media. AIChE Journal, 2000. 46(6): p. 1120–1130.
    [Google Scholar]
  8. Karimi-Fard, M. and A.Firoozabadi
    , Numerical Simulation of Water Injection in Fractured Media Using the Discrete-Fracture Model and the Galerkin Method. SPE Reservoir Evaluation & Engineering, 2003. 6(02): p. 117–126.
    [Google Scholar]
  9. Karimi-Fard, M., L.J.Durlofsky, and K.Aziz
    , An Efficient Discrete-Fracture Model Applicable for General-Purpose Reservoir Simulators. Society of Petroleum Engineers Journal, 2004. 9(02): p. 227–236.
    [Google Scholar]
  10. Geiger, S., et al.
    , Combining finite element and finite volume methods for efficient multiphase flow simulations in highly heterogeneous and structurally complex geologic media. Geofluids, 2004. 4(4): p. 284–299.
    [Google Scholar]
  11. Matthäi, S., et al.
    , Numerical simulation of multi-phase fluid flow in structurally complex reservoirs. Geological Society, London, Special Publications, 2007. 292(1): p. 405–429.
    [Google Scholar]
  12. Li, L. and S.H.Lee
    , Efficient Field-Scale Simulation of Black Oil in a Naturally Fractured Reservoir Through Discrete Fracture Networks and Homogenized Media. SPE Reservoir Evaluation & Engineering, 2008. 11(04): p. 750–758.
    [Google Scholar]
  13. Dershowitz, B., et al.
    , Integration of Discrete Feature Network Methods With Conventional Simulator Approaches. SPE Reservoir Evaluation & Engineering, 2000. 3(2): p. 165–170.
    [Google Scholar]
  14. Salimi, H. and J.Bruining
    , Improved Prediction of Oil Recovery From Waterflooded Fractured Reservoirs Using Homogenization. SPE Reservoir Evaluation & Engineering. 13(01): p. 44– 55.
    [Google Scholar]
  15. Gong, J. and W.R.Rossen
    , Modeling flow in naturally fractured reservoirs: effect of fracture aperture distribution on dominant sub-network for flow. Petroleum Science, 2016: p. 1–17.
    [Google Scholar]
  16. , Shape factor for dual-permeability fractured reservoir simulation: Effect of non-uniform flow in 2D fracture network. Fuel, 2016. 184: p. 81–88.
    [Google Scholar]
  17. Pooladi-Darvish, M. and A.Firoozabadi
    , Cocurrent and Countercurrent Imbibition in a Water-Wet Matrix Block. SPE Journal. 5(01): p. 3–11.
    [Google Scholar]
  18. Brooks, R.H. and A.T.Corey
    , Hydraulic properties of porous media and their relation to drainage design. Transactions of the ASAE, 1964. 7(1): p. 26–0028.
    [Google Scholar]
  19. Corey, A.T.
    , The interrelation between gas and oil relative permeabilities. Producers monthly, 1954. 19(1): p. 38–41.
    [Google Scholar]
  20. White, F.M.
    , Heat and Mass Transfer. 1988: Addison-Wesley.
    [Google Scholar]
  21. Bird, R.B., W.E.Stewart, and E.N.Lightfoot
    , Transport Phenomena. 2007: Wiley.
    [Google Scholar]
  22. Akker, H.E.A. and R.F.Mudde
    , Transport Phenomena: The Art of Balancing. 2014: Delft Academic Press.
    [Google Scholar]
  23. Rangel-German, E.R. and A.R.Kovscek
    , Experimental and analytical study of multidimensional imbibition in fractured porous media. Journal of Petroleum Science and Engineering, 2002. 36(1–2): p. 45–60.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201700352
Loading
/content/papers/10.3997/2214-4609.201700352
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