nerc.ac.uk

The robustness and general applicability of Optimal Resistivity Surveys designed by maximising model resolution

Wilkinson, P.B.; Chambers, J.E.; Meldrum, P.I.; Kuras, O.; Munro, C.J.. 2012 The robustness and general applicability of Optimal Resistivity Surveys designed by maximising model resolution. In: Near Surface 2012, Paris, France, 3-5 Sept 2012. EAGE.

Before downloading, please read NORA policies.
[img]
Preview
Text
Wilkinson et al 2012, Generic vs Model optimised surveys.pdf

Download (4MB) | Preview

Abstract/Summary

Most optimal survey design algorithms for resistivity imaging have not incorporated prior knowledge of the resistivity of the subsurface. The resulting surveys are optimal for a homogeneous earth, but little investigation has yet been carried out to test whether they are robust, i.e. that they remain optimal when applied to imaging heterogeneous subsurface resistivity distributions. This paper compares a generic survey, which is designed to maximise the estimated model resolution evenly across a homogeneous earth, with specific surveys similarly designed for a number of heterogeneous resistivity distributions. In terms of both the average estimated model resolution and the correlations between the inverted and true resistivity models, the generic and heterogeneous survey designs give near-identical results. This suggests that surveys designed using homogeneous earth approximations are robust in the presence of resistivity heterogeneities and are therefore generally applicable. Traditional dipole-dipole surveys with the same number of measurements do not give such good inverted images, and their degree of optimality (measured either by average resolution or image correlation) is less robust in the presence of heterogeneity.

Item Type: Publication - Conference Item (Paper)
NORA Subject Terms: Earth Sciences
Mathematics
Physics
Date made live: 27 Mar 2014 15:08 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/506726

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...