运用优化的算法提高油藏工程系统性能及开发作业已经有很长的历史并且很成功。同样,很多年来,优化方法通常是通过最小平方法一直用于地震处理。最近的研究已经集中在应用新一类的先进的优化方法作近地表静校正的计算、速度分析及地震反演等。在这篇论文中,我们将讨论使用这些优化技术中的一种——遗传算法(GA—genetic algo-rithms)的运算及其优越性。遗传算法可以解决大而复杂的问题。它能克服一些传统优化方法的不足。正如它的名字所说明的,下面用在遗传算法中的模型,就是基于生物遗传理论及达尔 The use of optimized algorithms to improve reservoir engineering system performance and development operations has a long history and is very successful. Similarly, for many years, optimization methods have been used for seismic processing, usually by the least-squares method. Recent research has focused on applying a new class of advanced optimization methods for near-surface static correction calculations, velocity analysis, and seismic inversion. In this paper, we discuss the use of GA-genetic algo-rithms and its advantages using one of these optimization techniques. Genetic algorithms can solve large and complex problems. It overcomes some of the shortcomings of traditional optimization methods. As its name implies, the following model used in genetic algorithms is based on the theory of biological genetics and Dahl