Share Email Print
cover

Proceedings Paper

Location and characterisation of magnetised objects using total-field borehole magnetic data
Author(s): Qing Zhang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Location and characterisation of magnetic objects from measured magnetic data has long been a research interest with the difficulty in handling the non-uniqueness in the inversion process. Ground-surface methods, which are widely used for objects buried in shallow depthes, become ineffective for those sinking into deep soil, because the anomaly field diminishes rapidly by distance and is heavily interfered by the metal debris distributed in the ground surface. A total-field borehole magnetometer can penetrate to such depths and collect relatively quiet data. However, conventional interpretation techniques suffer from the inherent non-uniqueness in the borehole dimension. In this paper, a constrained optimisation method is utilised for the interpretation of total-field borehole data for the detection of deeply buried objects. The major advantage over conventional techniques comes from the analytically-derived constraints imposed on the parameter vector by excluding the non-geosensible results from consideration and hence reducing the non-uniqueness to a minimal level. A test site has been developed for the evaluation using real world data. The interpretation results demonstrate its superior capability in handling real-world problems with high non-uniqueness. Furthermore, this method provides a way to estimate the moment strength without knowing the exact position. Together with the modelled signature data for different objects, characterisation of a particular item is possible from the inversion of a single total-field borehole profile.

Paper Details

Date Published: 19 October 2005
PDF: 10 pages
Proc. SPIE 5982, Image and Signal Processing for Remote Sensing XI, 598215 (19 October 2005); doi: 10.1117/12.627551
Show Author Affiliations
Qing Zhang, Univ. of Liverpool (United Kingdom)


Published in SPIE Proceedings Vol. 5982:
Image and Signal Processing for Remote Sensing XI
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top