1887

Abstract

Summary

Multidimensional problem of the petrophysical properties inversion is ill posed and strongly affected by noise and measurement errors. Stochastic simulation has become the most popular approach to obtain seismic reservoir characterization. Based on stochastic simulation, we proposed a probabilistic petrophysical properties inversion method. Prior distribution of the petrophysical variables, statistical rock-physics model, and stochastic simulation are used to determine the posterior distribution of the petrophysical properties. Statistical rock-physics modeling gives the relation between elastic and petrophysical variables. Conditional distributions of petrophysical properties are acquired by stochastic sampling and probability theory. Mathematical method is applied in the probabilistic method, which is applied successfully in AVO inversion. Advantage of stochastic sampling methods is that it correctly sample the target probability distribution even though the a-priori distribution is not defined in a closed form. Application of the proposed method to real data gives good results.

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/content/papers/10.3997/2214-4609.201900798
2019-06-03
2020-03-31
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References

  1. Aleardi, M., Ciabarri, F. and GarceaB.et al.
    [2015] Seismic reservoir characterization in offshore Nile Delta. Part I: Comparing different methods to derive a reliable rock-physics model. GNGTS, 11–19.
    [Google Scholar]
  2. [2015] Seismic reservoir characterization in offshore Nile Delta. Part II: Probabilistic petrophysical seismic inversion. GNGTS, 20–27.
    [Google Scholar]
  3. Avseth, P., Mukerji, T. and Mavko, G.
    [2005] Quantitative seismic interpretation: Applying rock physics tools to reduce interpretation risk. Cambridge University Press.
    [Google Scholar]
  4. Bachrach, R.
    [2006] Joint estimation of porosity and saturation using stochastic rock-physics modeling. Geophysics, 71(5): O53–O63.
    [Google Scholar]
  5. Bosch, M., Mukerji, T. and Gonzalez, E. F.
    [2010] Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review. Geophysics, 75(5): A165–A176.
    [Google Scholar]
  6. Doyen, P.
    [2007] Seismic reservoir characterization. EAGE. Expanded Abstracts.
    [Google Scholar]
  7. Grana, D.
    [2016] Bayesian linearized rock-physics inversion. Geophysics, 81(6): D625–D641.
    [Google Scholar]
  8. Grana, D. and Della Rossa, E.
    [2010] Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion. Geophysics, 75(3), O21–O37.
    [Google Scholar]
  9. Li, D. and ZhangF.
    [2015] Direct estimation of petrophysical properties based on AVO inversion. SEG, Expanded Abstracts, 2886–2890.
    [Google Scholar]
  10. Russell, B.
    [1988] Introduction to seismic inversion methods. SEG, Expanded Abstracts, 1–5.
    [Google Scholar]
  11. Xu, S. and WhiteR. E.
    [1995] A new velocity model for clay -sand mixtures. Geophysical Prospecting, 43(1): 91–118.
    [Google Scholar]
  12. Yang, P., Liu, S, and Mu, X.et al.
    [2014] A Novel Method for Direct Fluid Factor Extraction. SEG, Expanded Abstracts, 3174–3178.
    [Google Scholar]
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