近地表密度估计的重力贝叶斯分析方法及在云南地区的应用

牛源源, 郭良辉, 石磊, 陈石, 庄建仓. 2019. 近地表密度估计的重力贝叶斯分析方法及在云南地区的应用. 地球物理学报, 62(6): 2101-2114, doi: 10.6038/cjg2019M0332
引用本文: 牛源源, 郭良辉, 石磊, 陈石, 庄建仓. 2019. 近地表密度估计的重力贝叶斯分析方法及在云南地区的应用. 地球物理学报, 62(6): 2101-2114, doi: 10.6038/cjg2019M0332
NIU YuanYuan, GUO LiangHui, SHI Lei, CHEN Shi, ZHUANG JianCang. 2019. Estimation of near-surface density based on gravity Bayesian analysis and its application in Yunnan area. Chinese Journal of Geophysics (in Chinese), 62(6): 2101-2114, doi: 10.6038/cjg2019M0332
Citation: NIU YuanYuan, GUO LiangHui, SHI Lei, CHEN Shi, ZHUANG JianCang. 2019. Estimation of near-surface density based on gravity Bayesian analysis and its application in Yunnan area. Chinese Journal of Geophysics (in Chinese), 62(6): 2101-2114, doi: 10.6038/cjg2019M0332

近地表密度估计的重力贝叶斯分析方法及在云南地区的应用

  • 基金项目:

    中国地震局地球物理研究所基本科研业务费专项资助(DQJB18B03), 国家自然科学基金面上项目(41774098, 41874097, 41774090), 中国-东南亚毗邻区大震活动地球动力学研究(科技部国际合作项目, 2015DFA21206), 中央高校基本科研业务费专项资金和中国地震局震情跟踪面上课题(2018020201)联合资助

详细信息
    作者简介:

    牛源源, 女, 1994年生, 硕士在读研究生, 主要从事重磁数据处理与反演方法技术研究与应用.E-mail:iamnyy1001@163.com

    通讯作者: 郭良辉, 男, 教授, 主要从事地球物理数据精细处理与三维反演方法研究与应用.E-mail:guo_lianghui@163.com
  • 中图分类号: P631

Estimation of near-surface density based on gravity Bayesian analysis and its application in Yunnan area

More Information
  • 基于布格重力异常相对于地形起伏光滑分布的约束条件,从一维自由空气重力异常数据出发,采用贝叶斯方法估算近地表岩石密度,同时采用三次B样条函数拟合布格重力异常,获取光滑分布的布格重力异常.数据拟合和光滑约束之间的权重采用Akaike贝叶斯准则(ABIC准则)自动确定.均匀剖分模型和不均匀剖分模型数据试验都验证了该方法的有效性.相关参数评价表明,足够多的样条系数可以提高估计结果的准确性,样条系数的个数接近测点数时可获得较稳定的估计结果.增大异常的噪声水平时,ABIC准则可有效地自动增大先验光滑约束的权重.云南地区两条重力剖面应用结果表明,剖面沿线的近地表密度值起伏变化明显(达2.45~2.8 g·cm-3),前寒武纪和古生代地层密度相对较高(主要为2.53~2.75 g·cm-3),而中生代密度较低(2.45~2.73 g·cm-3);本文估计的近地表密度结果与区域物性资料及地表地质特征较吻合;估计的剖面布格重力异常具有光滑性;红河断裂两侧近地表密度差异较大,可达0.4 g·cm-3.本文获得的两条剖面近地表密度结构和布格重力异常为该区深部结构与构造研究提供更可靠的重力基础数据.

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  • 图 1 

    均匀剖分模型

    Figure 1. 

    Uniform partition model

    图 2 

    均匀剖分模型试验的超参数搜索图

    Figure 2. 

    The search path of hyperparameters in uniform partition model test (The hyperparameters are 8.78×10-5 and 4.11×10-1, and the minimum ABIC value was 244.31)

    图 3 

    均匀剖分模型试验的估计结果

    Figure 3. 

    The estimated results of uniform partition model

    图 4 

    非均匀剖分模型

    Figure 4. 

    Un-uniform partition model

    图 5 

    非均匀剖分模型试验的估计结果

    Figure 5. 

    The estimated result of non-uniform partition model

    图 6 

    (a) 最小ABIC值随M的变化情况;(b)估计标准差随M的变化情况

    Figure 6. 

    (a) The changes of the minimum ABIC value with the increase of M value; (b) The changes of the estimated standard deviation of data residual with the increase of M value

    图 7 

    各个子区块的估计密度值(A)及估计密度误差随M的变化情况(B)(黑色实心方形:估计值;黑色实线:理论值)

    Figure 7. 

    With the increase of M value, the changes of estimated density in each subdomain (A; black line with square: estimated value; black solid line: theoretical value) and estimated density error (B)

    图 8 

    不同噪声水平的原始自由空气异常对应的估计结果

    Figure 8. 

    Different estimated results of original Free-air anomaly with different noise level

    图 9 

    (a) 研究区地形图及(b)研究区地质构造简图

    Figure 9. 

    (a) The topography map of research area; (b) The geological structure sketch of research area

    图 10 

    两条重力剖面的已知信息及估计结果(左列:AA′剖面,右列:BB′剖面)

    Figure 10. 

    The known information and estimated results of two gravity profiles (left column: profile AA′, right column: profile BB′)

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出版历程
收稿日期:  2018-12-26
修回日期:  2019-03-25
上线日期:  2019-06-05

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