Compared with traditional gravity measurement data, gravity gradient tensor data contain more high frequency information, which can be used to understand the earth's interior structure, mineral resources distribution etc. In this study, the authors present an algorithm for inverting gravity gradiometer data to recover the three-dimensional (3-D) distributions of density. Spatial gradient weighting was used to constrain the extent of the body horizontally and vertically. A more accurate inversion result can be obtained by combining the prior information into the weighting function and applying it in inversion. This method was tested on synthetic models and the inverted results showed that the resolution was significantly improved. Moreover, the algorithm was applied to the inversion of empirical data from a salt dome located in Texas, USA, which demonstrated the validity of the proposed method.
Abstract
Compared with traditional gravity measurement data, gravity gradient tensor data contain more high frequency information, which can be used to understand the earth's interior structure, mineral resources distribution etc. In this study, the authors present an algorithm for inverting gravity gradiometer data to recover the three-dimensional (3-D) distributions of density. Spatial gradient weighting was used to constrain the extent of the body horizontally and vertically. A more accurate inversion result can be obtained by combining the prior information into the weighting function and applying it in inversion. This method was tested on synthetic models and the inverted results showed that the resolution was significantly improved. Moreover, the algorithm was applied to the inversion of empirical data from a salt dome located in Texas, USA, which demonstrated the validity of the proposed method.
关键词
gravity gradient data /
spatial gradient weighting /
3-D inversion
Key words
gravity gradient data /
spatial gradient weighting /
3-D inversion
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基金
Supported by Project of Natural Science Fund of Jilin Province (No.20180101312JC).
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