Magnetic Inversion and Regional Tectonics of the Dabie Orogen

Abstract

Physical property inversion techniques are the methods to reveal the internal structures of Earth’s lithosphere. In this study, we introduce an Occam-type inversion algorithm into a spherical coordinate system, and invert the magnetization based on the three-component magnetic anomalies. The synthetic model tests show that the inversion effects of the vertical components are relatively stable, while the anti-noise ability is strong. We apply the algorithm to a set of vertical component anomalies derived from the satellite magnetic field model and obtain Dabie orogen 3D magnetization distribution. Multiple magnetic sources are identified within the orogen and adjacent areas, and the related tectonic evolution processes are analyzed. The significant magnetization characteristics of the orogen can be associated with mantle upwelling caused by the Early Cretaceous lithospheric delamination, along with the partial melting of the mafic–ultramafic lower crust that had not participated in the delamination. The magnetic sources near the Mozitan–Xiaotian fault, and those located in the western Dabie area, are also restricted by Mesozoic and Jurassic–Cretaceous deep melt activities, respectively. The study provides evidence for the suture line position of the plate subduction in the deep lithosphere. Furthermore, the results display certain indications of mineralization activities in the middle–lower Yangtze Valley metallogenic belt.

Geobody estimation by Bhattacharyya method utilizing nonlinear inverse modeling of magnetic data in Baba-Ali iron deposit, NW Iran

“…Zong et al [ 76 ] reviewed the inversion algorithms proposed to process multi-dimensional magnetic resonance datasets in different scenarios. Zhang et al [ 77 ] applied three-component magnetic anomalies, introduced an Occam-type inversion algorithm into a spherical coordinate system, and inverted the magnetization. Eventually, for the inversion of magnetic anomalies caused by dykes, a social spider optimization (SPO) algorithm was developed to decipher the source body properties tested with synthetic anomalies corrupted by different levels of random noise and field anomalies [ 35 , [78] , [79] , [80] ].…”