基于地质体空间位置优化约束的航空重力梯度数据三维物性反演

张楠, 吴燕冈, 周帅, 孙鹏飞. 2019. 基于地质体空间位置优化约束的航空重力梯度数据三维物性反演. 地球物理学报, 62(4): 1515-1525, doi: 10.6038/cjg2019M0626
引用本文: 张楠, 吴燕冈, 周帅, 孙鹏飞. 2019. 基于地质体空间位置优化约束的航空重力梯度数据三维物性反演. 地球物理学报, 62(4): 1515-1525, doi: 10.6038/cjg2019M0626
ZHANG Nan, WU YanGang, ZHOU Shuai, SUN PengFei. 2019. 3D inversion of airborne gravity gradient data for physical properties based on optimizing constraints of spatial position of the geologic body. Chinese Journal of Geophysics (in Chinese), 62(4): 1515-1525, doi: 10.6038/cjg2019M0626
Citation: ZHANG Nan, WU YanGang, ZHOU Shuai, SUN PengFei. 2019. 3D inversion of airborne gravity gradient data for physical properties based on optimizing constraints of spatial position of the geologic body. Chinese Journal of Geophysics (in Chinese), 62(4): 1515-1525, doi: 10.6038/cjg2019M0626

基于地质体空间位置优化约束的航空重力梯度数据三维物性反演

  • 基金项目:

    国家重点研发计划课题(2017YFC0602203),国家青年科学基金项目(41604069),博士后创新人才支持计划和中国博士后科学基金面上资助项目(2018M630323)联合资助

详细信息
    作者简介:

    张楠, 男, 1981年生, 博士研究生, 主要从事航空重磁探测方法及数据处理技术的研究.E-mail:juanveron@sohu.com

    通讯作者: 周帅, 男, 1988年生, 讲师, 主要从事移动平台探测数据处理与解释方法研究.E-mail:zhoushuai@jlu.edu.cn
  • 中图分类号: P631

3D inversion of airborne gravity gradient data for physical properties based on optimizing constraints of spatial position of the geologic body

More Information
  • 重力数据的物性反演面临着严重的多解性问题,降低多解性的有效手段是加入约束条件.而边界识别、深度估计及成像方法可获取地质体的水平位置、深度范围等几何参数信息,本文将基于数据本身挖掘的地质体几何参数信息约束到物性反演中,以降低反演的多解性.通过引入基于深度信息的深度加权函数及基于水平位置的水平梯度加权函数建立优化约束条件,有效地提高了反演结果的横向及纵向分辨率.重力梯度数据包含更多的地质体空间特征信息,将优化约束反演方法应用到全张量数据的反演中,模型试验表明本文方法反演结果与理论模型更加吻合.最后对美国路易斯安那州文顿盐丘实测航空重力梯度数据的应用表明,本文方法在其他地球物理、地质资料不足的情况下获得更可靠的反演结果.

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  • 图 1 

    棱柱体模型空间位置

    Figure 1. 

    Spatial position of a prism model

    图 2 

    含噪重力异常及其梯度异常

    Figure 2. 

    Noise-bearing gravity and its gradient anomalies of the prism

    图 3 

    传统深度加权函数的反演结果

    Figure 3. 

    Inversion result with traditional depth-weighting function

    图 4 

    归一化总梯度成像结果

    Figure 4. 

    Imaging result of normalized full gradients

    图 5 

    基于先验深度信息约束的深度加权函数反演结果

    Figure 5. 

    Inversion result with depth-weighting function constrained by a prior depth information

    图 6 

    深浅棱柱体模型空间位置

    Figure 6. 

    Spatial position of the model with deep and shallow prisms

    图 7 

    传统反演方法和优化约束反演方法对比

    Figure 7. 

    Comparison between the traditional inversion method and the optimized constrained method

    图 8 

    归一化边界识别方法成像结果

    Figure 8. 

    Imaging result of normalized edge identification method

    图 9 

    实测航空重力全张量数据

    Figure 9. 

    Measured airborne gravity full tensor data

    图 10 

    斜导数深度估计方法结果

    Figure 10. 

    Depth estimated by tilted derivative method

    图 11 

    优化约束物性反演结果

    Figure 11. 

    Optimized constrained inversion result

    图 12 

    优化约束物性反演结果切片图

    Figure 12. 

    Slices of optimized constrained inversion for physical property

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出版历程
收稿日期:  2018-11-02
修回日期:  2019-02-18
上线日期:  2019-04-05

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