1887
Volume 32, Issue 3-4
  • ISSN: 0812-3985
  • E-ISSN: 1834-7533

Abstract

Magnetic inversion programs such as mag3d from the University of British Columbia’s Geophysical Inversion Facility (UBC-GIF) have proven to be very useful for generating realistic 3D susceptibility models from surface Total Magnetic Intensity (TMI) data.

These programs do not perform well when the observed data includes the response of bodies which are strongly remanently magnetised. This failure occurs because the forward model algorithm used in the inversion only generates the induced response, so the remanent component in the TMI has to be modeled using the induced response for an unrealistic distribution of susceptibility.

In this paper we introduce two transforms: the analytic signal of the vertical integral (ASVI) and the vertical integral of the analytic signal (VIAS). When applied to TMI data, these transforms produce data which is qualitatively similar to a purely induced TMI response for a vertical magnetic field. We investigate the effectiveness of using mag3d to invert the ASVI for a synthetic dataset and the VIAS for a real TMI dataset. For both datasets we find that the inversion of the transformed data produces a model which is much more realistic than that obtained by inverting the TMI data.

Loading

Article metrics loading...

/content/journals/10.1071/EG01238
2001-09-01
2026-01-22
Loading full text...

Full text loading...

References

  1. MacLeod, I. N., Jones, K. and Dai, T. F., 1993, 3-D analytic signal in the interpretation of total magnetic field data at low magnetic latitudes, Exploration Geophysics, 24, 679-688.
  2. Li, Y. and Oldenburg, D. W., 1996, 3-D inversion of magnetic data: Geophysics, 61, no. 02, 394-40
/content/journals/10.1071/EG01238
Loading
  • Article Type: Research Article
Keyword(s): 3D magnetic inversion; analytic signal; remanence; vertical integral

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error