1887
  1. Home
  2. Conferences
  3. Conference Proceedings
  4. ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery
  5. Conference paper

Abstract

Summary

The main challenge for predictive simulation of carbonate reservoirs is associated with large uncertainties in the geological characterization with multiple features including fractures and cavities. This type of reservoirs requires robust and efficient forward-simulation capabilities to apply data assimilation or optimization technique under uncertainties. The interaction between reservoir matrix and various features introduces a complex multi-scale flow response driven by global boundary conditions. The Discrete Fracture Models (DFM), which represent fractures explicitly, is capable to accurately depict all important features of flow behavior. However, these models are constrained by many degrees of freedom when the fracture network becomes complicated. The Embedded DFM, which represents the interaction between matrix and fractures analytically, is an efficient approximation. However, it cannot accurately reproduce the effect of local flow conditions, especially when the secondary fractures are present. In this study, we applied a numerical upscaling of DFM a triple continuum model where large features are represented explicitly using the numerical EDFM and small features are upscaled as a third continuum. In this approach, we discretize the original geo-model with unstructured grid based on DFM and associate the mesh geometry with large features in the model. Using the global solution, we generate local boundary conditions for the model capturing the response of primary features to the flow. Applying local boundary conditions, we resolve all secondary features using a fine scale solution and update the local boundary conditions. This procedure is applied iteratively using the local-global-upscaling formalism. To demonstrate the accuracy of the Multi-Level Discrete Fracture Model, several realistic cases have been tested. By comparing with fine scale DFM solution and the traditional EDFM technique, we demonstrate that the proposed model is accurate enough to capture the flow behavior in complex fractured systems with advanced computational efficiency.

© EAGE Publications BV
Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201802164
2018-09-03
2024-04-25

  • From This Site

    /content/papers/10.3997/2214-4609.201802164
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. BarenblattG. I, ZheltovIu. P , KochinaI. N.
    , 1960. Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks. Journal of Applied Mathematics and Mechanics24(5), 1286–1303.
     [Google Scholar]
  2. Chen, Y., Durlofsky, L. J., Gerritsen, M., Wen, X. H.
    , 2003. A coupled local-global upscaling approach for simulating flow in highly heterogeneous formations. Advances in Water Resources26(1): 1041–1060.
     [Google Scholar]
  3. CMG
    , 2013. IMEX User Guide. Version 2013. Calgary, Canada.
     [Google Scholar]
  4. Durlofsky, L. J., Chen, Y.
    , 2012. Uncertainty quantification for subsurface flow problems using coarse-scale models. In I. G.Graham, T. Y.Hou, O.Lakkis, and R.Scheichl, editors, Numerical Analysis of Multiscale Problem, Lecture Notes in Computational Science and Engineering, 163–202.
     [Google Scholar]
  5. Eclipse Technical Description
    , 2009. Schlumberger Simulation Software Manuals.
     [Google Scholar]
  6. GallyamovE., GaripovT., VoskovD., van den HoekP.
    , 2018. Discrete fracture model for simulating waterflooding processes under fracturing conditions, Int J Numer Anal Methods Geomech, doi:10.1002/nag.2797
     https://doi.org/10.1002/nag.2797 [Google Scholar]
  7. Garipov, T. T., Tomin, P., Rin, R., VoskovD. V., TchelepiH. A.
    2018. Unified thermo-compositional-mechanical framework for reservoir simulation. Computational Geosciences. https://doi.org/10.1007/s10596-018-9737-5
     [Google Scholar]
  8. Garipov, T.T., Karimi-Fard, M., Tchelepi, H.A.
    , 2016. Discrete fracture model for coupled flow and geomechanics, Computational Geosciences, 20 (1), pp. 149–160. DOI: 10.1007/s10596‑015‑9554‑z
     https://doi.org/10.1007/s10596-015-9554-z [Google Scholar]
  9. Geuzaine, C., Remacle, J. F.
    , 2009. Gmsh: a three-dimensional finite element mesh generator with built-in pre- and post-processing facilities. International Journal for Numerical Methods in Engineering79(11), 1309–1331.
     [Google Scholar]
  10. Gerke, H. H., van Genuchten, M. T.
    , 1993a. A dual-porosity model for simulating the preferential movement of water and solutes in structured porous media. Water Resources Research29: 305–319.
     [Google Scholar]
  11. , 1993b. Evaluation of a first-order water transfer term for variably saturated dual-porosity flow models. Water Resources Research29: 1225–1238.
     [Google Scholar]
  12. Gong, B.
    , 2007. Effective models of fractured systems. Standford.
     [Google Scholar]
  13. Hajibeygi, H., Karvounis, D., Jenny, P.
    , 2011. A hierarchical fracture model for the iterative multiscale finite volume method. Journal of Computational Physics230(24): 8729–8743.
     [Google Scholar]
  14. Karimi-Fard, M., Durlofsky, L. J.
    , 2016. A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geo-logical features. Advances in Water Resources96(6), 354–372.
     [Google Scholar]
  15. Karimi-Fard, M., Durlofsky, L.
    , 2012. Accurate resolution of near-well effects in upscaled models using flow-based unstructured local grid refinement. SPE Journal1084–1095.
     [Google Scholar]
  16. Karimi-Fard, M., Durlofsky, L. J., Aziz, K.
    , 2004. An efficient discrete fracture model applicable for general-purpose reservoir simulators. SPE Journal9(2), 227–236.
     [Google Scholar]
  17. Karimi-Fard, M., Gong. B., Durlofsky, L.
    , 2006. Generation of coarse-scale continuum flow models from detailed fracture characterizations. Water Resources Research42(10), W10423.
     [Google Scholar]
  18. Lee, S. H., Jensen, C. L., Lough, M. F.
    , 2000. Efficient finite-difference model for flow in a reservoir with multiple length-scale fractures. SPE Journal5(3), 268–275.
     [Google Scholar]
  19. Li, L., Lee, S. H.
    , 2008. Efficient Field-Scale Simulation of Black Oil in a Naturally Fractured Reservoir Through Discrete Fracture Networks and Homogenized Media. SPE Journal750–758.
     [Google Scholar]
  20. Miller, C. T., Christakos, G., Imhoff, P. T., et al.
    , 1998. Multiphase flow and transport modeling in heterogeneous porous media: challenges and approaches. Advances in Water Resources21: 77–120.
     [Google Scholar]
  21. Pruess, K., Narasimhan, T. N.
    , 1982. On fluid reserves and the production of superheated steam from fractured, vapor-dominated geothermal reservoirs. Journal Geophysical Research87(B11), 9329–9339.
     [Google Scholar]
  22. , 1985. A practical method for modeling fluid and heat flow in fractured porous media, SPE Journal25(1), 14–26.
     [Google Scholar]
  23. Renard, P., de Marsily, G.
    , 1997. Calculating effective permeability: a review, Advances in Water Resources20: 253–278.
     [Google Scholar]
  24. Sartori, A.
    , 2018. Uncertainty Quantification Based on Hierarchical Representation of Fractured Reservoirs. TU Delft. Schlumberger Market Analysis, 2007.
     [Google Scholar]
  25. Tene, M., Bosma, S. B., Al Kobaisi, M. S., Hajibeygi, H.
    , 2017. Projection-based Embedded Discrete Fracture Model (pEDFM). Advances in Water Resources105, 205–216.
     [Google Scholar]
  26. Jene, M., Wang, Y., Hajibeygi, H.
    , 2015. Adaptive algebraic multiscale solver for compressible flow in heterogeneous porous media. Journal of Computational Physics300: 679–694.
     [Google Scholar]
  27. Voskov, D.
    , 2012. An extended natural variable formulation for compositional simulation based on tie-line parameterization. Transport in porous media92(3), 541–557.
     [Google Scholar]
  28. Wang, Y., Hajibeygi, H., Tchelepi, H.
    , 2014. Algebraic multiscale solver for flow in heterogeneous porous media. Journal of Computational Physics259: 284–303.
     [Google Scholar]
  29. Warren, J. E., Root, P. J.
    , 1963. The behavior of naturally fractured reservoirs. SPE Journal245–255.
     [Google Scholar]
  30. Zaydullin, R., Voskov, D.V., James, S.C., Henley, H., Lucia, A.
    , 2014. Fully compositional and thermal reservoir simulation, Computers and Chemical Engineering, 63, pp. 51–65. DOI: 10.1016/j.compchemeng.2013.12.008
     https://doi.org/10.1016/j.compchemeng.2013.12.008 [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201802164
Loading
Multi-Level Discrete Fracture Model For Carbonate Reservoirs
Conference Proceedings 2018, 1 (2018); https://doi.org/10.3997/2214-4609.201802164
/content/papers/10.3997/2214-4609.201802164
/content/papers/10.3997/2214-4609.201802164
Loading

Data & Media loading...

Most Cited This Month Most Cited RSS feed

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