Magnetization vector inversion using Gaussian radial basis functions for equivalent grid optimization: Imaging the magma conduit system of the Xiangshan area (NW China)
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ID: 313595
2026
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Abstract
Summary Magnetization vector inversion is an effective method for analyzing magnetic anomaly data influenced by significant remanent magnetization. However, the multi-dimensional parameters of the magnetization vector increase both the non-uniqueness of the solutions and the computational burden. We propose a magnetization vector inversion method based on Gaussian radial basis function which the magnetization vector parameters are represented by the functional node parameters. By leveraging the inherent smoothness and local support characteristics of Gaussian radial basis function, the method suppresses spurious divergence in magnetization direction during the inversion process, thereby enhancing both the accuracy and computational efficiency of the inversion results. The proposed method is applied to interpret magnetic data in Xiangshan area for revealing the magnetization characteristics of magma-hydrothermal structures. The region of non-uniform magnetization vectors, which can be interpreted as lithological contacts and alteration fronts, may indicate multiple phases of magmatic intrusion. The distinct magnetization directions between shallow mineralized bodies and underlying magma conduits facilitates the identification of potential mineralized rocks and magma conduits that are undetectable by conventional magnetic intensity analysis. Drilling in the study area confirms the presence of Cu-Ni mineralization in the shallow mafic-ultramafic intrusions. Results demonstrate that the magnetization vector inversion could capture complex geological information, providing a promising tool for understanding volcanic and magmatic systems.
| Reference Key |
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| Authors | Xiangdong Li, Shuang Liu, Banxiao Ruan, Liu W, Zhenhua Zhou, 蔡红柱, Xiangyun Hu |
| Journal | geophysical journal international |
| Year | 2026 |
| DOI |
10.1093/gji/ggag186
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| URL | |
| Keywords | Keywords not found |
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