1887

Abstract

Summary

Cluster analysis based on the shape of seismic traces allows perform zonation of the field area, similar to the facial division. The project proposes to carry out research which includes the allocation of clusters relying on forward seismic models with different impulse frequency. in this way it will be possible to make a conclusion about influence of quality of seismic acquisition on zonation of the area of study. It is proposed to perform investigations on large scale field model based on proportions of fluvial deposits outcrop.

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/content/papers/10.3997/2214-4609.201900528
2019-03-25
2024-04-25
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References

  1. ChopraS., MarfurtK. J.
    , 2007. Seismic attributes for prospect identification and reservoir characterization: Society of Exploration Geophysicists and European Association of Geoscientists and Engineers.
    [Google Scholar]
  2. DemyanovV., BelozerovV., BaranovV.
    , 2015. Prospectivity evaluation by seismic trace form classification.
    [Google Scholar]
  3. FedorovaE., BukhanovN., BaranovV.
    , 2015. Synthetic seismic models construction for detailed geological outcrop description. EAGE, Th P 03.
    [Google Scholar]
  4. PodboronovD.
    , 2004. Geological modeling approach of fluvial – deltaic reservoirs based on outcrop analogue study.
    [Google Scholar]
  5. ReinfeldsI., NansonG.
    , 1993. Formation of braided river floodplains, Waimakariri River, New Zealand.
    [Google Scholar]
  6. RukavishnikovV., KurelenkovS.
    , 2012. Dynamic cluster analysis for updating simulation model using time-lapse seismic.
    [Google Scholar]
  7. SongC. et al.
    , 2017. Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means. J. Geophys. Eng. 141535.
    [Google Scholar]
  8. WronaT. et al.
    , 2017. Seismic facies analysis using machine-learning. Geophysics, GEO-2017- 0595.R2.
    [Google Scholar]
  9. ZhaoT. et al.
    , 2015. A comparison of classification techniques for seismic facies recognition.
    [Google Scholar]
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