nerc.ac.uk

Computation of Optimized Arrays for 3-D Electrical Imaging Surveys

Loke, M.H.; Wilkinson, P.B.; Chambers, J.. 2013 Computation of Optimized Arrays for 3-D Electrical Imaging Surveys. In: Near Surface 2013, Bochum, Germany, 9-11 Sep 2013. EAGE.

Before downloading, please read NORA policies.
[thumbnail of Loke et al 2013, 3D array optimisation.pdf]
Preview
Text
Loke et al 2013, 3D array optimisation.pdf

Download (1MB) | Preview

Abstract/Summary

Three-dimensional surveys and inversion models are required to accurately resolve structures in areas with very complex geology where 2-D models might suffer from artifacts. Many 3-D surveys use a survey grid where the number of electrodes along one direction (x) is much greater than in the perpendicular direction (y). Frequently, due to limitations in the number of independent electrodes in the multi-electrode system, the surveys use a roll-along system with a small number of parallel survey lines aligned along the xdirection. The 'Compare R' array optimization method previously used for 2-D surveys is adapted for such 3-D surveys. Offset versions of the inline arrays used in 2-D surveys are included in the number of possible arrays (the comprehensive data set) to improve the sensitivity to structures in between the lines. By using PCs with modern graphics cards incorporating a fast Graphics Processing Unit (GPU) and using an improved single-precision 'Compare R' algorithm, the 3-D optimized arrays can be calculated within a reasonable time despite the comprehensive data set possibly have millions of arrays. A comparison with data sets using inline measurements made using conventional arrays show that structures located between the lines are much better resolved with the optimized arrays.

Item Type: Publication - Conference Item (Paper)
NORA Subject Terms: Earth Sciences
Mathematics
Physics
Date made live: 27 Mar 2014 13:43 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/506720

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...