• DocumentCode
    2229044
  • Title

    Seismic thin bed responses and thickness approximations

  • Author

    Li, Qiang ; Gao, Jinghuai

  • Author_Institution
    Inst. of Wave & Inf., Xi´´an Jiaotong Univ., Xi´´an, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6063
  • Lastpage
    6066
  • Abstract
    Seismic thin bed thickness approximation has been a hot topic for many years in seismic data processing. The variation of bed thickness can usually indicate some geologic structure anomalies. Generally it´s difficult to distinguish and estimate the thin bed when the thickness is below the tuning thickness (resolution limit). But there is a close relationship between bed thickness and its frequency domain response characteristics. Both of the reflectivity series and seismic wavelet influence the thin bed frequency response. Peak frequency attribute of two common bed types is studied and an analytical expression of thickness and peak frequency is obtained through different order of estimate. The influence of random noise is also discussed. The synthesized model results demonstrate the effectiveness of our proposed method. In the real data applications, this method should be combined with many other preprocessing operations.
  • Keywords
    geology; geophysical techniques; random noise; seismology; analytical expression; bed types; frequency domain response characteristics; geologic structure anomalies; peak frequency; preprocessing operations; random noise; real data applications; reflectivity series; resolution limit; seismic data processing; seismic thin bed thickness approximation; seismic wavelet; thin bed frequency response; tuning thickness; Approximation methods; Equations; Frequency domain analysis; Frequency estimation; Mathematical model; Noise; Reflectivity; Seismic attributes; approximation; bed thickness; frequency response; peak frequency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6352224
  • Filename
    6352224