摘要
地震反演问题常常需要一些非线性全局最优化的方法。近年来 ,基于生物学、物理学、人工智能和一些非线性科学而发展了一些具有全局优化性能且通用性强的随机搜索算法 ,如 :遗传算法、模拟退火、禁忌搜索和混沌搜索等。作者主要针对地震勘探反演问题的应用综述了这四种非线性随机优化方法的原理和特点 ,并对它们的性能作了一定的分析和比较。
Seismic inversion problems must be solved by non linear global optimization methods. In recent years, some non linear stochastic optimistic algorithms are developed by biology, physics, artificial intelligence and nonlinear science, such as Genetic algorithm, Simulated annealing, Tabu searching and Chaos searching et al. In this paper, the principles and characteristics of four stochastic optimistic algorithms are summarized, and their performances are analyzed and compared on the applications of seismic inversion problems.
出处
《物探化探计算技术》
CAS
CSCD
2001年第1期6-10,共5页
Computing Techniques For Geophysical and Geochemical Exploration
基金
"油气藏地质与开发工程"国家重点实验室开放基金! (PLN970 37)
西南石油学院院科技基金!资助项目 (Y15 5 )
