Bayesian推断理论下基于柯西分布的速度反演方法

Bayesian推断理论下基于柯西分布的速度反演方法

论文摘要

地震反演问题本质上是一个统计学反问题,可以通过贝叶斯推断归纳成一个非线性的数学反演问题。传统的做法是将观测数据与模拟数据的误差默认为满足高斯分布,并通过噪音计算高斯分布中的均值和方差。该方法最终是针对高斯分布的指数项的一个优化问题。上述一系列近似和优化导致反演的不准确性。本文为从Bayesian理论出发,对地震反演问题进行进一步分析理论基础更加坚实;通过利用概率分布函数与误差的线性关系,减弱针对模型参数反演的非线性;并通过选择不同误差的度量方式来体现对反演问题的强针对性;此外,根据模拟并结合最大似然估计得到概率分布函数参数,可以得到更准确的反演问题的描述方式。模型试算证明了本文方法的准确性。

论文目录

  • 引言
  • 1 理论方法
  •   1.1 基于Bayesian理论的地震反演问题
  •   1.2 分布函数下对参数反演的非线性
  •   1.3 不同度量方式的讨论
  • 2. 数值模拟
  • 3. 结论
  • 文章来源

    类型: 国内会议

    作者: 蔺玉曌,李振春,张凯

    关键词: 分布,柯西分布,非线性,速度反演

    来源: 2019年油气地球物理学术年会 2019-11-27

    年度: 2019

    分类: 基础科学,工程科技Ⅰ辑

    专业: 地质学,地球物理学,矿业工程

    单位: 中国石油大学(华东)地球科学与技术学院

    分类号: P631.4

    DOI: 10.26914/c.cnkihy.2019.022998

    页码: 534-537

    总页数: 4

    文件大小: 467k

    下载量: 19

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    Bayesian推断理论下基于柯西分布的速度反演方法
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