• DocumentCode
    2715111
  • Title

    Simulated annealing for pattern detection and seismic analysis

  • Author

    Huang, Kou-Jen ; Huang, Kou-Yuan ; Wang, Luke K. ; Chou, Ying-Liang ; Hsieh, Yueh-Hsun ; Hsieh, Shan-Chih

  • Author_Institution
    Dept. of Electr. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
  • fYear
    2009
  • fDate
    14-19 June 2009
  • Firstpage
    1278
  • Lastpage
    1285
  • Abstract
    Simulated annealing (SA) is adopted to detect the parameters of line, circle, ellipse, and hyperbola. The equation of pattern is defined under translation and rotation. The distance from all points to all patterns is defined as the system error. Also we use the minimum error to determine the number of patterns. The parameters of the pattern are learned with probability in SA. The proposed SA parameter detection system can search a set of parameter vectors for the global minimal error. In the seismic experiments, the system can well detect line of direct wave and hyperbola of reflection wave in the real seismic data. In the seismic data processing, the reflection curves on common depth reflection point (CDP) gathers are hyperbolic patterns. So using SA, the parameters of each hyperbolic pattern can be detected. The parameters are used to calculate the root-mean-squared velocity Vrms. The Vrms is used to the normal-moveout (NMO) correction and stacking to reconstruct the image of the subsurface. Using the result of SA hyperbolic parameter detection, it is a novel method in the seismic velocity analysis.
  • Keywords
    geophysical signal processing; image reconstruction; least mean squares methods; object detection; probability; seismic waves; seismology; simulated annealing; common depth reflection point; direct wave; global minimum error; hyperbolic pattern detection; image reconstruction; normal-moveout correction; parameter detection; probability; reflection wave; root-mean-squared velocity; seismic data processing; seismic velocity analysis; simulated annealing; Analytical models; Computer science; Data processing; Equations; Image reconstruction; Neural networks; Pattern analysis; Reflection; Simulated annealing; Stacking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2009. IJCNN 2009. International Joint Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-3548-7
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2009.5179090
  • Filename
    5179090