摘要
A global optimized algorithm is developed in this study for dealing with the problems of nonlinearity and multiparameter characteristics of the residual statics correction method. Integration of the simulated annealing approach with the uniform design optimized method makes the updating of the model more reasonable and therefore,increases the speed of searching for the global optimimzed solution. A procedure is proposed for selecting the temperature parameters of different model components and the process of decreasing the temperature. Here the selection of the temperature parameter is correlated with seismic energy, which makes the algorithm having a self-adapted characteristic. This new algorithm overcomes several shortcomings of the conventional simulated annealing method. Its application to seismic data shows that the algorithm developed in this study is more efficient than the conventional simulated annealing method.
A global optimized algorithm is developed in this study for dealing with the problems of nonlinearity and multiparameter characteristics of the residual statics correction method. Integration of the simulated annealing approach with the uniform design optimized method makes the updating of the model more reasonable and therefore,increases the speed of searching for the global optimimzed solution. A procedure is proposed for selecting the temperature parameters of different model components and the process of decreasing the temperature. Here the selection of the temperature parameter is correlated with seismic energy, which makes the algorithm having a self-adapted characteristic. This new algorithm overcomes several shortcomings of the conventional simulated annealing method. Its application to seismic data shows that the algorithm developed in this study is more efficient than the conventional simulated annealing method.
出处
《地球物理学报》
SCIE
EI
CAS
CSCD
北大核心
2002年第5期707-713,共7页
Chinese Journal of Geophysics
基金
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关键词
静校正
模拟退火
均匀设计
非线性反演
地震勘探
Statics corrections, Simulated annealing, Uniform design,Nonlinear inversion.