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Exploration Geophysics Exploration Geophysics Society
Journal of the Australian Society of Exploration Geophysicists
RESEARCH ARTICLE

Contact mapping from gridded magnetic data ? a comparison of techniques

M. Pilkington and P. Keating

Exploration Geophysics 35(4) 306 - 311
Published: 2004

Abstract

Delineating the edges of magnetized bodies is a fundamental application of magnetic data to geological mapping in areas of limited exposure. Especially in Pre-Cambrian shield-like regions, locating lateral changes in magnetization of the outcropping crystalline rocks provides spatial information that is crucial in extending mapped geology into sparsely exposed or completely covered areas. Although not all magnetic contacts correspond to lithological contacts, the former provide key information on structural regimes, deformation styles and trends, and magnetic texture. Many techniques for contact mapping have been developed, some originally based on profile (2D) data and others designed specifically for grid-based (3D) data sets. Here, we evaluate five methods applied to gridded data. The first three are based on finding maxima of the horizontal gradient magnitude of the total field (TF-hgm), tilt (TI-hgm), and pseudogravity (PSG-hgm). The fourth and fifth methods rely on locating maxima of the analytic signal (AS) and the 3D local wavenumber (LW). Method TF-hgm produces theoretically correct contact locations only when the data is reduced to the pole, and even then may produce false or secondary solutions mimicking contact trends. Method TI-hgm is less sensitive to field direction but also suffers from secondary maxima. Method PSG-hgm is perhaps the most established approach of those mentioned, and in the case of vertical contacts produces reliable maxima, however knowledge of magnetization direction is required. Method AS and LW theoretically produce maxima directly over contacts and are insensitive to magnetization direction and body dip but are more sensitive to noise than the other three methods, which limits their application to higher-quality data sets.

https://doi.org/10.1071/EG04306

© ASEG 2004

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