地球物理学进展 ›› 2019, Vol. 34 ›› Issue (6): 2320-2327.doi: 10.6038/pg2019CC0452

• 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

基于小波细节信息的重力源参数估算

汤井田1, 2, 杨磊1, 2, 任政勇1, 2, *, 胡双贵1, 2, 钟乙源1, 2, 杨智1, 2   

  1. 1. 中南大学地球科学与信息物理学院,长沙 410083;
    2. 中南大学,有色金属成矿预测与地质环境监测教育部重点实验室,长沙 410083
  • 收稿日期:2019-01-12 修回日期:2019-06-17 出版日期:2019-12-20 发布日期:2019-12-29
  • 通讯作者: 任政勇,男,1983年生,教授,博士生导师,从事重磁电正演和反演研究.(E-mail: renzhengyong@csu.edu.cn)
  • 作者简介:汤井田,男,1965年生,教授,博士生导师,主要从事电磁场理论和应用、地球物理信号处理及反演成像等研究.(E-mail:jttang@csu.edu.cn)
  • 基金资助:
    国家自然科学基金重点项目(41830107); 湖南省研究生科研创新项目(CX20190084)联合资助.

Gravity source parameters estimation based on wavelet details information

TANG Jing-tian1, 2, YANG Lei1, 2, REN Zheng-yong1, 2, *, HU Shuang-gui1, 2, ZHONG Yi-yuan1, 2, YANG Zhi1, 2   

  1. 1. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China;
    2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring of Ministry of Education, Central South University, Changsha 410083, China
  • Received:2019-01-12 Revised:2019-06-17 Online:2019-12-20 Published:2019-12-29

摘要: 小波多尺度分析方法在位场数据处理领域得到了广泛关注.目前,人们对利用该方法分离位场数据所得到的小波细节横向边缘信息认知不够深入,有必要做进一步探究.本文首先采用小波多尺度位场分离方法分离出区域和局部重力异常,然后利用haar小波变换HVD模法对局部异常信息进行多尺度分析,将所得到的小波细节信息进行水平、垂直和对角线方向分解,探测出局部异常体的横向边缘特征,并利用频谱分析方法估测出场源深度.最后,通过理论模型和南非Witwatersrand Basin航空实测重力数据进行分析,表明小波多尺度分析方法不仅能很好地实现位场分离、近似提取异常体场源深度,还可以利用小波细节信息有效地分辨出局部异常体的横向边缘特征,提高其识别精度.

关键词: 重力异常, 小波多尺度分析, 小波细节, 场源深度, 横向边缘特征

Abstract: Wavelet multi-scale analysis method has received extensive attention in the field of geophysical data processing. Currently, it is necessary to further explore the application of wavelet detail information based on the lack of understanding horizontal edge information of wavelet details. In this paper, the regional and local gravity anomalies were firstly separated by the wavelet multi-scale analysis, then the local anomaly information was analyzed again using the haar wavelet transform HVD method, besides, the obtained wavelet details were decomposed horizontally, vertically and diagonally. The characteristics of the lateral edges of the local anomaly were analyzed, moreover, the depth of the field source was estimated using the spectrum analysis method. Finally, through the theoretical model and the airborne measured gravity data of the Witwatersrand Basin in South Africa, it's shown that wavelet multi-scale analysis can not only realize the separation of the potential field well, but also estimate the depth of source field. What's more, it can also distinguish the lateral edge features of the local anomalies by using the wavelet detail information effectively, and improve its recognition accuracy.

Key words: Gravity anomaly, Wavelet multi-scale analysis, Wavelet details, Depth of source field, Edge features

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