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Generalisation and improvement of the compact gravity inversion method

Zhu Wenwu, Peng Junhuan, Luo Sanming, Meng Xiangang, Liu Jinzhao, Zhu Chuandong

Acta Geophysica

2020

Vol. 68, no. 6

1667--1677

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 efciency, 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 fexibility than CGI, selecting an appropriate compactness factor α and depth weighting function β is difcult, and we design a parameter selection rule to search the proper α and β quantitively. Furthermore, we improve RCGI for boasting superior computational efciency 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 efciency than RCGI and CGI, which increases with the number of iterations.