The bedrock electrical conductivity map of the UK

Beamish, David. 2013 The bedrock electrical conductivity map of the UK. Journal of Applied Geophysics, 96. 87-97. https://doi.org/10.1016/j.jappgeo.2013.06.001

Full text not available from this repository. (Request a copy)

Official URL: http://dx.doi.org/10.1016/j.jappgeo.2013.06.001

Abstract/Summary

Airborne electromagnetic (AEM) surveys, when regionally extensive, may sample a wide-range of geological formations. The majority of AEM surveys can provide estimates of apparent (half-space) conductivity and such derived data provide a mapping capability. Depth discrimination of the geophysical mapping information is controlled by the bandwidth of each particular system. The objective of this study is to assess the geological information contained in accumulated frequency-domain AEM survey data from the UK where existing geological mapping can be considered well-established. The methodology adopted involves a simple GIS-based, spatial join of AEM and geological databases. A lithology-based classification of bedrock is used to provide an inherent association with the petrophysical rock parameters controlling bulk conductivity. At a scale of 1:625k, the UK digital bedrock geological lexicon comprises just 86 lithological classifications compared with 244 standard lithostratigraphic assignments. The lowest common AEM survey frequency of 3 kHz is found to provide an 87% coverage (by area) of the UK formations. The conductivities of the unsampled classes have been assigned on the basis of inherent lithological associations between formations. The statistical analysis conducted uses over 8 M conductivity estimates and provides a new UK national scale digital map of near-surface bedrock conductivity. The new baseline map, formed from central moments of the statistical distributions, allows assessments/interpretations of data exhibiting departures from the norm. The digital conductivity map developed here is believed to be the first such UK geophysical map compilation for over 75 years. The methodology described can also be applied to many existing AEM data sets.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.jappgeo.2013.06.001
ISSN:	09269851
Date made live:	09 Aug 2013 10:51 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/502932

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.jappgeo.2013.06.001

ISSN:

09269851

Date made live:

09 Aug 2013 10:51 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/502932