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An Investigation of l p -Norm Minimization for the Artifact-Free Inversion of Gravity Data.

Authors :
Li, Zelin
Yao, Changli
Source :
Remote Sensing. Jul2023, Vol. 15 Issue 14, p3465. 12p.
Publication Year :
2023

Abstract

The l2-norm minimization is a common means for the 3D inversion of gravity data. The unconstrained l2-norm inversion will produce a smooth solution, which contains redundant structures and artifacts. Positivity-constrained l2-norm inversion can eliminate redundant structures and artifacts, resulting in a more reliable solution. However, the positivity constraint restricts the applications of gravity inversion to some extent because the measured gravity data are likely to be caused by both positive and negative sources. To address this issue, we propose a strategy that combines the lp-norm regularization and fine adjustment of the depth weighting function to refine the unconstrained gravity inversion results. Synthetic tests show that the proposed strategy yields an improved smooth solution compared with the unconstrained l2-norm inversion method. The proposed strategy is also applied to the inversion of gravity data collected over a Layikeleke iron–copper skarn deposit, Xinjiang, China. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
14
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
169700804
Full Text :
https://doi.org/10.3390/rs15143465