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基于模拟退火和遗传算法的剩余静校正方法研究

Research of Residual Static Correction Using Simulated Annealing and Genetic Algorithm

【作者】 田连玉

【导师】 张军华;

【作者基本信息】 中国石油大学 , 地球探测与信息技术, 2007, 硕士

【摘要】 静校正是贯穿于复杂地表地区地震勘探资料采集和处理中的一项十分关键的基础性工作。当地震资料信噪比比较低或者剩余静校正量大于地震波周期的一半时,为防止出现“周波跳跃”现象,这时就必须用全局优化方法寻求解决剩余静校正问题。论文首先详细阐述了静校正方法的分类及剩余静校正的非线性特点,介绍了模拟退火算法和遗传算法的基本原理及特点;其次,研究了二维观测系统的几何位置关系并设计了优化算法的目标函数;随后,分析了模拟退火和退火遗传算法的参数选择方案,将两种算法应用到理论模型及实际地震资料,静校正后叠加剖面的分辨率明显提高,层位连续性明显加强;最后,总结了论文编写过程中自己对静校正问题及优化算法的一点认识和建议。论文的关键工作在于:为减少算法的计算量,消除“周波跳跃”现象,选用超长道集的互相关作为优化算法的目标函数;利用模拟退火一步法来解决剩余静校正问题;结合模拟退火算法的思想,对遗传算法的目标函数进行尺度变换,实现退火遗传算法剩余静校正。

【Abstract】 In complex surface areas, residual static correction is a pivotal and basic work, which is essential to seismic data acquisition and processing. When the S/N ratio is low or the residual statics are larger than half of the wavelet period, residual statics must be resolved by optimization methods to avoid the“cycle-skips”phenomenon.The paper firstly formulates classifications of static correction methods and the nonlinear characteristics of residual static correction. Then the basic principles and characteristics of the simulated annealing and genetic algorithm are introduced. Secondly, the geometry relations of 2D survey is studied and the objective functions of the optimization algorithm are designed. Subsequently, after analyzing the schemes of parameter selections, the simulated annealing and hybrid genetic algorithm are applied to theoretical models and practical seismic data, which makes both resolutions of the stacked profiles and continuity of the layers enhanced. Finally, a little sentiment about static correction and optimization algorithm is summarized during this period.In this paper, super-trace crosscorrelation is used as objective function to avoid“cycle-skips”and reduce computations. Secondly, the“heat bath”algorithm is used to calculate statics. Thirdly, combined with simulated annealing algorithm, the fitness function is scaled to implement hybrid genetic algorithm for static correction. All of this three points are the key work of this paper.

  • 【分类号】P631.4
  • 【被引频次】4
  • 【下载频次】388
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