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Abstract

Summary

In naturally fractured reservoirs characterization and modelling, a key fracture parameter is fracture density. Classically, fracture density along well trajectories is estimated from image log data interpretation using various methods and applying corrections to account for 1D sampling bias. Various methods and concepts are then used to extrapolate/interpolate the fracture density beyond the well control. The well density data are often assumed to be hard data (precisely known). It has been showed, however, that this should not be the case. Consequently, estimating fracture density uncertainty is a key issue in fracture modelling.

Methods have been proposed to estimate fracture density and related uncertainty but they are based on assumptions (fractures nearly parallel to the borehole, randomly distributed fractures) that are always met. The fracture density can also be controlled by many different geological constraints: fracture clustering, bed thickness, stress shadow effect...

This paper presents a methodology to simulate DFN that can be controlled by various types of geological constraints in order to assess the uncertainty attached to wells drilled through the simulated DFN. Uncertainty tables are generated, which can then be applied to well fracture data in real NFR reservoirs.

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.201800025
2018-02-05
2024-04-18

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References

  1. Barthélémy, J.F., Guiton, L.M.E. and Daniel, J.M.
    [2009], Estimates of fracture density and uncertainties from well data. Int. J. Rock Mech. & Min. Sci., 46, 590–603.
     [Google Scholar]
  2. Bisdom, K., Gauthier, B. D. M., Bertotti, G. and Hardebol, N. J.
    [2014] Calibrating discrete fracture-network models with a carbonate threedimensional outcrop fracture network: Implications for naturally fractured reservoir modeling. AAPG Bulletin, 98 (7), 1351–1376.
     [Google Scholar]
  3. Bonneau, F., Caumon, G. Renard, P., and Sausse, J.
    [2012] Stochastic sequential simulation of genetic-like discrete fracture networks, proceedings of 32nd GOCAD Meeting.
     [Google Scholar]
  4. Garcia, M.H., Gouth, F., and Gosselin, O.
    [2007] Fast and efficient modeling and conditioning of naturally fractured reservoir models using static and dynamic data, SPE 107525, presented at the SPE Europec/EAGE Annual Conference, London, UK.
     [Google Scholar]
  5. Gauthier, B.D.M., Garcia, M.H., and Daniel, J.M.
    [2002] Integrated Fractured Reservoir Characterization: A Case Study in a North Africa Field, SPE Res. Eval. and Engr., 284–294.
     [Google Scholar]
  6. Ladeira, F.L., and Price, N.J.
    [1981]. Relationship between fracture spacing and bed thickness. Journal of Structural Geology3, 179–183.
     [Google Scholar]
  7. Lamarche, J., Chabani, A. and Gauthier, B.D.M.
    , Process of fracture linkage and hooking. Journal of Structural Geology, In press.
     [Google Scholar]
  8. Narr, W.
    [1996] Estimating Average Fracture Spacing in Subsurface Rock. AAPG Bulletin, 80 (10), 1565–1586.
     [Google Scholar]
  9. Peacock, D.C.P.
    [2006] Predicting variability in joint frequencies from boreholes. Journal of Structural Geology28 (2006) 353–361.
     [Google Scholar]
  10. Stoyan, D., Kendall, W. S., & Mecke, J.
    [1987] Stochastic geometry and its applications. Wiley.
     [Google Scholar]
  11. Terzaghi, R. D.
    [1965] Sources of error in joint surveys. Géotechnique, 15 (3), 287–304.
     [Google Scholar]
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DFN Simulation to Quantify Fracture Density Uncertainty in Wells. Impact of Some Typical Geological Constraints
Conference Proceedings 2018, 1 (2018); https://doi.org/10.3997/2214-4609.201800025
/content/papers/10.3997/2214-4609.201800025
/content/papers/10.3997/2214-4609.201800025
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