• DocumentCode
    1496391
  • Title

    New Method of Horizon Recognition in Seismic Data

  • Author

    Lili Li ; Guoqing Ma ; Xiaojuan Du

  • Author_Institution
    Coll. of Geo-Exploration Sci. & Technol., Jilin Univ., Changchun, China
  • Volume
    9
  • Issue
    6
  • fYear
    2012
  • Firstpage
    1066
  • Lastpage
    1068
  • Abstract
    Horizon recognition is a valuable tool in the interpretation of seismic data. In this letter, we present a new method which uses the combination of horizontal derivative and mathematical morphology to identify horizons. We first use a threshold value to filter the horizontal derivative of seismic data and then use the ratio of the erosion of the filtered derivative to the dilation of the filtered derivative to balance the amplitudes of strong and weak horizons. Finally, we move the strong amplitude to the position of the actual horizon. This method is demonstrated on both synthetic and real data. The resolving power of the new method is evaluated by comparing the results with those obtained by other similar methods. The new method can display the horizons more clearly.
  • Keywords
    geophysical techniques; seismology; erosion ratio; filtered derivative dilation; horizon recognition method; horizontal derivative morphology; mathematical morphology; seismic data; Cellular neural networks; Image edge detection; Morphology; Multiresolution analysis; Robustness; System-on-a-chip; Horizon recognition; horizontal derivatives; mathematical morphology; seismic data;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2012.2190039
  • Filename
    6184283