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
Link To Document