1887

Abstract

Summary

The fast modeling of gamma-gamma density well logging is essential for the inversion techniques of formation properties, which is usually carried out jointly with other logging measurements and it also can help to adjust the initial geological model in real time during drilling. The Monte Carlo method is the foremost numerical technique to simulate gamma-gamma density logging measurement. But due to its low calculation speed, it is not sufficient for inversion or real-time forward modeling. An algorithm to achieve the fast simulation of density logging response is introduced. In the algorithm, a new approximation model is proposed to enable the forward modeling of density logging more accurate and efficient. The Monte Carlo simulation method is utilized as benchmarks to validate the performance of the fast simulation method. The density logging responses under vertical and horizontal well conditions are simulated. The results of the fast simulation show a good agreement with the Monte Carlo simulations. In addition, the comparison of density imaging data also confirmed the accuracy of the fast simulation method.

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/content/papers/10.3997/2214-4609.201901073
2019-06-03
2024-04-19
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References

  1. Coueet, B., Watson, C.
    , 1992. Applications of Monte Carlo differential neutron sensitivity calculations to geophysical measurements. Transactions of the American Nuclear Society65, 5–6.
    [Google Scholar]
  2. Efnik, M., Hamawi, M., Al Shamri, A., Madjidi, A., Shade, C.
    , 1999. Using new advances in LWD technology for geosteering and geologic modeling, SPE/IADC Middle East Drilling Technology Conference. Society of Petroleum Engineers.
    [Google Scholar]
  3. Ellis, D.V., Singer, J.M.
    , 2007. Well logging for earth scientists. Springer.
    [Google Scholar]
  4. Fang, S., Wang, T.
    , 2000. Accurate Born simulation of induction response using an optimal background, SEG Technical Program Expanded Abstracts 2000. Society of Exploration Geophysicists, pp. 1806–1809.
    [Google Scholar]
  5. Gardner, R.P., Liu, L.
    , 1999. Monte Carlo simulation of neutron porosity oil well logging tools: Combining the geometry-independent fine-mesh importance map and one-dimensional diffusion model approaches. Nuclear science and engineering133, 80–91.
    [Google Scholar]
  6. Mendoza, A., Torres-Verdín, C., Preeg, B.
    , 2010a. Linear iterative refinement method for the rapid simulation of borehole nuclear measurements: Part 2—High-angle and horizontal wells. Geophysics75, E79–E90.
    [Google Scholar]
  7. , 2010b. Linear iterative refinement method for the rapid simulation of borehole nuclear measurements: Part I—Vertical wells. Geophysics75, E9–E29.
    [Google Scholar]
  8. Mendoza, A., Torres-Verdín, C., Preeg, W.
    , 2007. Rapid simulation of borehole nuclear measurements with approximate spatial flux-scattering functions, 48th Annual Logging Symposium. Society of Petrophysicists and Well-Log Analysts.
    [Google Scholar]
  9. Watson, C.
    , 1992. A spatial sensitivity analysis technique for neutron and gamma-ray measurements. Transactions of the American Nuclear Society65, 3–4.
    [Google Scholar]
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