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

A novel approach to comparing AEM inversion results with borehole conductivity logs

Niels B. Christensen 1 3 Kenneth C. Lawrie 2
+ Author Affiliations
- Author Affiliations

1 University of Aarhus, Hoegh Guldbergs Gade 2, DK8210 Aarhus C, Denmark.

2 Strategic Groundwater Science, Groundwater Branch, Environmental Geoscience Division, Geoscience Australia, Canberra, ACT 2601, Australia.

3 Corresponding author. Email: nbc@geo.au.dk

Exploration Geophysics 49(3) 309-322 https://doi.org/10.1071/EG17029
Submitted: 7 March 2017  Accepted: 3 May 2017   Published: 7 June 2017

Abstract

Borehole conductivity logs, besides being useful for identifying, interpreting and correlating geological formations, also find widespread use as auxiliary information in the inversion of airborne electromagnetic (AEM) data. One of the quality checks often applied to AEM inversion results is a comparison between the conductivity structures revealed by borehole conductivity logs in the survey area and the AEM inversion model closest to the borehole, often called an ‘FID point comparison’.

Another use of borehole conductivity logs is found in modern AEM inversion procedures, where the borehole conductivity information is included as prior information in a laterally constrained inversion. In most former and present practices, AEM layer conductivities are compared with the measured conductivity in the borehole. However, the borehole conductivity is essentially an apparent conductivity – it is a measured data value – while the AEM layer conductivities are model parameters resulting from inverting AEM data. To avoid comparing data and model parameters we suggest a conceptually clear approach based on an inversion of the borehole conductivity data to obtain a borehole conductivity model, which in turn can be compared with the AEM model. Furthermore, the AEM forward response of the borehole model can, in a consistent way, be compared with the AEM data. In both approaches, we keep track of uncertainty and define quantitative, uncertainty-normalised measures of the difference between borehole and AEM values, and we find simple functional relationships between the two. The methodology is demonstrated on the AEM data and conductivity logs of the Broken Hill Managed Aquifer Recharge (BHMAR) project.

Key words: airborne, borehole constrained inversion, borehole log, comparison, electromagnetic.


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