A new method to integrate different gravity gradient components in reweighted regularized inversion with a minimum support constraint. Issue 2 (20th February 2019)

• Record Type: Journal Article
• Authors: Qin, Pengbo; Xiang, Min; Liang, Xin; Hou, Zhenlong
• Is Part Of: Geophysical journal international. Volume 217:Issue 2(2019)
• Page Start: 1387
• Page End: 1412
• Publication Date: 2019-02-20
• Subjects: Geopotential theory -- Gravity anomalies and Earth structure -- North America -- Inverse theory -- Joint inversion; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggz095
• Languages: English
• ISSNs: 0956-540X

Abstract

SUMMARY: The gravity gradient tensor has been increasingly used in practical applications. Among them, how to extract information contained in different gravity gradient components is a challenging problem. Gravity gradient joint inversion is one effective method to solve this problem. We integrate different gravity gradient components in a matrix and then apply them in inversion directly. In this paper, we modify the method to get a new gravity gradient joint inversion (NGGJI). The method is based on the reweighted regularized inversion. We choose one component, for example, g zz, and use the other components to build a weighting matrix. Then we apply the weighting matrix in g zz inversion. We present the method to construct the weighting matrix based on a single component and multiple components. We analyse the characteristics of different weighting matrices and the noise effects on weighting matrices. We compare the inversion results obtained from the conventional gravity gradient joint inversion (CGGJI) with the inversion results obtained from the NGGJI. We conclude that the NGGJI's requirement for memory storage is lower and the resolution of the NGGJI inversion results is higher. We apply the method to survey data from Vinton Salt Dome, Louisiana, USA. The results have proved to be consistent with known geological information.