An AI approach to automated magnetic formation mapping beneath cover

David A. Pratt; K. Blair McKenzie; Anthony S. White

doi:10.1080/22020586.2019.12073001

2nd Australasian Exploration Geoscience Conference: Data to Discovery

ISSN: 2202-0586
E-ISSN:

oa An AI approach to automated magnetic formation mapping beneath cover
Authors David A. Pratt^a, K. Blair McKenzie^b and Anthony S. White^c
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^a Tensor Research P/L, PO Box 5189 Greenwich, NSW, 2065, Australia, [email protected] ^b Tensor Research P/L, PO Box 5189 Greenwich, NSW, 2065, Australia, [email protected] ^c Tensor Research P/L, PO Box 5189 Greenwich, NSW, 2065, Australia, [email protected]
Publisher: Australian Society of Exploration Geophysicists
Source: ASEG Extended Abstracts, Volume 2019, Issue 2nd Australasian Exploration Geoscience Conference: Data to Discovery, Dec 2019, p. 1 - 9
DOI: https://doi.org/10.1080/22020586.2019.12073001
- Published online: 01 Dec 2019

Abstract

Summary

Most regional scale magnetic maps are dominated by the magnetic characteristics of steeply dipping basement units truncated by an unconformity surface. It is easy to demonstrate that 80 to 90% of each total field magnetic anomaly is contributed by this intersecting surface. We approach this problem by mapping the boundaries between contrasting magnetic units along each line in the magnetic survey using the full precision of the line data and 3D information from the magnetic gradient tensor. Additionally, we derive the azimuth of each boundary, depth to the unconformity and magnetic properties of the anomalous units. The segments are overlain on any image such as existing geological maps, satellite imagery, gravity or magnetic imagery to provide a new geological interpretation concept. This method provides a new way to interpret new and old magnetic surveys.

Eigenvector analysis of the magnetic tensor and normalised source strength (NSS) are combined with an artificial intelligence (AI) approach to estimate the basement properties. The method is applied to full tensor magnetic survey data or a grid of the total magnetic intensity data is processed using FFT transformations to derive the magnetic gradient tensor. These data are used as input to the pre-trained AI process for calculation of depth, width, azimuth, magnetic susceptibility and magnetisation direction. The rock properties and depth information can be used for 3D visualisation of the unconformity and 2D mapping of the magnetic lithology of the unconformity surface.

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References

Bates,M., and Dennis, J., 2018, PACE Gawler Craton Airborne Geophysical Survey Program: Block 3B – Torrens, SGL Technical Report (unpublished) 218p.
Beike, M., Clark, D.A., Austin, J.R. and Foss, C.A. 2012, Estimating source location using normalized magnetic source strength calculated from magnetic gradient tensor data: Geophysics, 77, (6), J23-J37.
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Clark, D.A., 2012, New methods for interpretation of magnetic vector and gradient tensor data I: eigenvector analysis and the normalised source strength: Exploration Geophysics, 43, 267-282.
Foss, C.A., Gouthas, G., Fabris, A., Werner, M., Katona, L., Hutchens, M. and Reed, G. 2018, Gawler Craton Airborne Geophysical Survey Region 3B, Torrens – Enhanced geophysical imagery and magnetic source depth models. Report Book 2018/00038, Government of South Australia, 76p.
McKenzie, K.B., 2019, The magnetic tensor of a triaxial ellipsoid, its derivation and its application to the determination of magnetisation direction (Exploration Geophysics, in press).
Pedersen, L.B. and Rasmussen, T.M., 1990, The gradient tensor of potential field anomalies: Geophysics, 55 (12), 1558-1566.
Pratt, D.A., McKenzie, K.B., White, A.S., Foss, C.A., Shamin, A. and Shi, Z. 2001, A User Guided Expert System Approach to 3D Interpretation of Magnetic Anomalies. Extended Abstracts, ASEG 15th Geophysical Conference and Exhibition, August 2001, Brisbane.
Pratt, D.A., 2013, The potential of remote remanence estimation (RRE) for kimberlite exploration – A case history from the Thomson Fold Belt. Extended Abstracts, 23rd International Geophysical Conference and Exhibition, 11-14 August 2013 - Melbourne, Australia.
Pratt, D.A., McKenzie, K.B. and White, A.S., 2014, Remote remanence estimation (RRE). Exploration Geophysics, 45(4), 314-323.
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/content/journals/10.1080/22020586.2019.12073001

Article Type: Research Article

Keyword(s): AI; basement; magnetic; mapping; tensor

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oa An AI approach to automated magnetic formation mapping beneath cover

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