西南石油大学学报(自然科学版) ›› 2006, Vol. 28 ›› Issue (5): 26-28.DOI: 10.3863/j.issn.1000-2634.2006.05.007

• 地质勘探 • 上一篇    下一篇

波阻抗混合优化反演方法研究

彭才 朱仕军 孙建库2 扬洪德2 黄东山2 赵振伟

  

  1. 1.西南石油大学资源与环境学院,四川 成都 610500; 2.四川石油管理局地球物理勘探公司
  • 收稿日期:2005-10-27 修回日期:1900-01-01 出版日期:2006-10-20 发布日期:2006-10-20
  • 通讯作者: 彭才

RESEARCH ON METHOD OF MIXED OPTIMUM IMPEDANCE INVERSION

PENG Cai ZHU Shi-jun SUN Jian-ku et al   

  1. Southwest Petroleum University, Chengdu Sichuan 610500,China
  • Received:2005-10-27 Revised:1900-01-01 Online:2006-10-20 Published:2006-10-20
  • Contact: PENG Cai

摘要: 遗传算法是一种具有全局优化的随机搜索算法,针对遗传算法存在局部搜索能力差,求解精度不高等缺点,引入了模式搜索算法,利用模式搜索算法较强的局部搜索能力和较高的求解精度弥补遗传算法的不足。即利用遗传算法来控制寻优过程,用模式搜索算法使解快速逼近极小点,然后再用遗传算法使解逃脱局部极值,从而达到全局寻优目的。理论模型和实例计算分析验证了该方法的有效性

关键词: 波阻抗, 混合优化, 遗传算法, 模式搜索, 反演

Abstract: The genetic algorithm is a stochastic search method of global optimization, but also it has the disadvantages of low local search ability and precision. In order to solving the disadvantages this paper introduces pattern search, using the strong local search ability and high precision of pattern search to offset it. First of all, using generitc algorithm to compute a number of generations, and take all searched points as the first points of pattern search, then quicken convergent velocity. The analysis of theorized model and example computing validate the method of mixed optimum algorithm.


Key words: impedance, mixed optimization, generitc algorithm, pattern search, inversion

中图分类号: