1887

Abstract

Summary

Deep-water turbidities reservoir is a kind of the important reservoir that support the world reserves and production growth. As a kind of typical gravity flow deposition, deep-water turbidities reservoir shows the characteristics of server lateral variation and vertical multi-stage superimposition, demonstrating the frequent movement and migration of deep-water rivers. All these features make it difficult to identify the lateral reservoir boundary and divide the vertical depositional stage, thus directly influencing the development well pattern deployment, well location optimization and improvement of injection-production relationship. In order to solve these problems and reduce the risk of development, a new inversion method named self-facies-control pre-stack inversion is proposed. Via self-facies-control low frequency model construction and amplitude preserved factor adoption, the spatial resolution of the reservoir is improved. The high-precision inversion results provide important basis for fine lateral boundary identification of turbidity reservoir and vertical depositional stage division. The application of the method in A oilfield shows that the self facies-control pre-stack inversion method achieves good application effects in deep-water turbidities reservoir, and the spatial resolution of the inverted reservoir is effectively improved.

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/content/papers/10.3997/2214-4609.201701248
2017-06-12
2024-04-25
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References

  1. A. J.Berkhout, C. P.A.Wapenarr
    . Frequency formation of linear inversion [M]. The 57th SEG annual meeting, Petroleum industry Press, 1989.
    [Google Scholar]
  2. VeekenP C H, SilvaM D.
    Seismic inversion methods and some of their constrains[J]. First Break, 2004, 22(1):47∼70.
    [Google Scholar]
  3. SingletonS.
    The effects of seismic data conditioning on pre-stack simultaneous impedance inversion[J]. The Leading Edge, 2009, 28 (1): 772∼781.
    [Google Scholar]
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