地球物理学进展 ›› 2018, Vol. 33 ›› Issue (5): 2076-2082.doi: 10.6038/pg2018BB0558

• 应用地球物理学Ⅰ(油气及金属矿产地球物理勘探) • 上一篇    下一篇

基于DEXP的位场模型初步反演

张琦(),于平(),张代磊,林松   

  1. 吉林大学地球探测科学与技术学院,长春 130021
  • 收稿日期:2017-12-15 修回日期:2018-08-07 出版日期:2018-10-20 发布日期:2019-01-11
  • 通讯作者: 于平 E-mail:zhangqi0524@qq.com;yuping@jlu.edu.cn
  • 作者简介:张琦,男,1992年生,黑龙江哈尔滨人,硕士研究生,主要研究方向为固体地球物理学.
  • 基金资助:
    吉林省自然科学基金项目(20180101312JC)

Preliminary inversion of the potential field model based on DEXP

ZHANG Qi(),YU Ping(),ZHANG Dai-lei,LIN Song   

  1. College of Geoexploration Science and Technology, Jilin University, Changchun 130021, China
  • Received:2017-12-15 Revised:2018-08-07 Online:2018-10-20 Published:2019-01-11
  • Contact: Ping YU E-mail:zhangqi0524@qq.com;yuping@jlu.edu.cn

摘要:

位场成像技术能够快速计算出异常体的三维空间图像,是重磁数据解释中重要的工具.虽然该类方法计算速度快,方法简单、稳定,但通常不如反演方法能够给出场源的真实物性参数模型,成像的结果通常是与场源物性参数成比例的等效参数并且存在较为发散的缺点.本文以DEXP法为例对其成像原理进行说明,然后对其成像结果进行改进以克服传统成像方法存在的问题.首先将DEXP成像结果值转换为场源的初始物性参数模型,然后引入一种加权函数迭代更新物性模型从而实现对位场模型的初步反演过程.通过模型试验与实测数据的应用,证明本文方法相对于传统的DEXP法能够更精确的勾画出异常体的分布,并能够获得较为真实的物性参数.

关键词: DEXP, 快速成像, 重力梯度, 三维反演

Abstract:

Imaging of potential fields is a power interpretation tool, which yields a fast 3D representation of the source distribution of potential fields. Imaging methods are characterized by fast computation, stability, and simplicity, the results are quantities proportional or related to the source distribution (magnetization or density), but not the real physical properties. Inversion of potential field data can always determine the real physical parameters distribution but they are computationally expensive. Many imaging methods are based on multiscale methods allowing the source parameters of potential fields to be estimated from a simultaneous analysis of the field at various scales or, in other words, at different altitudes, so such source images are often smooth and too extended, reflecting the loss of spatial resolution for increasing altitudes. In this paper, we introduce a traditional imaging method called the “Depth from Extreme Points” (DEXP) and make an improvement over it. At first, we transform the DEXP result into source-parameter units by determining a constant by a linear regression of the observed field versus the field computed from the DEXP image. And then, we propose a weighting function to iterate physical property model to realize a preliminary inversion for potential field data. At last, we apply the improved method into synthetic model and real measured data, the results show that the new method can determine the physical property distributions of the causative bodies well, and the effectiveness also be verified.

Key words: DEXP, fast imaging, gravity gradient, 3D inversion

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