3d Magnetic Modelling And Inversion Incorporating Self-demagnetisation And Interactions
P.K. Fullagar and G.A. Pears
Event name: 13th SAGA Biennial Conference & Exhibition
Session: Session 8 B – Geophysical data processing
Publication date: 06 October 2013
Info: Extended abstract, PDF ( 330.1Kb )
Self-demagnetisation can significantly reduce the amplitude and alter the orientation of magnetisation in highly magnetic bodies, thereby modifying the observed magnetic field, sometimes substantially. In tabular bodies, for example, the transverse magnetisation is reduced, with the result that the magnetisation vector rotates towards the plane of the body. Furthermore, when highly magnetic bodies are in close proximity, the assumption of uniform inducing field is violated. Highly magnetic bodies can modify the local magnetic field appreciably, with the result that the magnetisation induced in one susceptible body is affected by the magnetisations of all its neighbours. It is important to take such interactions between highly magnetic bodies into account. Potential field modelling and inversion software “VPmg” has been upgraded to account for self demagnetisation and interaction between magnetic bodies. The algorithm computes H-field perturbations at the model cell centres in two stages: initialisation and optimisation. During initialisation, a demagnetisation tensor is estimated for each cell, from which a first estimate for the H-field perturbation is derived. During optimisation, the H-field field estimate is refined iteratively via an inversion procedure. Remanence is taken into account as well as induced magnetisation. The algorithm has been validated for homogeneous spheres, spheroids, slabs, and cylinders. It has also reproduced magnetic interactions between two horizontal cylinders, previously published by Hjelt. Explicit verification for complex heterogeneous bodies requires a suitable independent algorithm for benchmarking. The application to inversion in a highly magnetic environment is illustrated in a field data example.