Compact gravity inversion (CGI) is widely used to invert gravity data following the principle of minimising the volume of the causative body due to its simplicity, high efficiency, and sharp-boundary inversion results. In this study, the compactness weighting function is generalised and the depth weighting function is introduced to CGI to obtain the reweighted CGI (RCGI) method. Although RCGI exhibits better flexibility than CGI, selecting an appropriate compactness factor α and depth weighting function β is difficult, and we design a parameter selection rule to search the proper \(\alpha\) and \(\beta\) quantitively. Furthermore, we improve RCGI for boasting superior computational efficiency by gradually eliminating the model blocks that reach the designated boundaries in the iterative algorithm of inversion. This approach is termed the reweighted and element-elimination CGI (REECGI) method. The inversion results show that both RCGI and REECGI result in better inversion accuracy than CGI, and REECGI has higher computational efficiency than RCGI and CGI, which increases with the number of iterations.
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We would like to thank Prof. Shi Chen of the Institute of Geophysics, China Earthquake Administration for providing field data as well as specific guidance. We also thank Prof. Bofeng Guo of Tianjin University for offering constructive comments and editing the manuscript. Further, we would like to thank Editage (www.editage.cn) for English language editing.
This research was funded by the National Key R & D Program of China, Grant Nos. 2018YFC1503606 and 2017YFC1500501.
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The authors declare no conflict of interest.
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Zhu, W., Peng, J., Luo, S. et al. Generalisation and improvement of the compact gravity inversion method. Acta Geophys. (2020). https://doi.org/10.1007/s11600-020-00495-0
- Compact gravity inversion
- Inversion theory
- Compactness factor
- Weighting function
- Inversion accuracy
- Computational efficiency