Modelling the airborne electromagnetic response of a vertical contact David Annetts 1 Fred Sugeng 2 James Macnae 3 Art Raiche 4 Key Words: Airborne electromagnetics, conductivity contrast, numerical modelling ABSTRACT Airborne electromagnetic (AEM) surveying is an important exploration tool because it can map conductivity variations over large areas at a fraction of the cost of ground survey methods. Using rapid but approximate techniques, large volumes of data may be processed to show the variation of conductivity with depth beneath the survey. These approximate methods work well in regions with horizontal layering, but in certain circumstances they can imply the presence of false conductors in the vicinity of 2D and 3D structures. By comparing the AEM response of several 2.5D models, each of which contains a lateral conductivity contrast, we show that artefacts associated with conductivity contrasts can imply the presence of a false conductor when flight direction is towards the area of greater conductivity. When flight direction was away from the area of greater conductivity artefacts associated with the lateral conductivity contrast implied a false resistor. These artefacts were of sufficiently high magnitude that they masked the response of a genuine conductor (1.0 Ω.m) at a depth of 50 m. We show that multiple-component data sets utilising the inherent directional dependence qualities of AEM prospecting systems can be used to minimise interpretational errors in the presence of lateral conductivity contrasts. INTRODUCTION Airborne electromagnetic (AEM) surveys are excellent for mapping conductivity distributions over large areas. Interpreted data may be used to map salt scalds or as part of a mineral exploration programme. However, AEM data pose special challenges for interpretation, because typical surveys can easily accumulate over 2GB of data in as little as 3 hours (Lane et al., 1998). In principle, one could invert the survey data as a whole for a multidimensional conductivity distribution, e.g., Alumbaugh and Newman (1998). However, formally inverting survey data for a 1D Earth is a formidable task that would take many months, and multidimensional inversion is considerably more difficult (Ellis, 1998). With this in mind, much effort has been invested in so- called 'rapid approximate' techniques. Variously called conductivity-depth imaging (CDI) or conductivity-depth transforms (CDT) in the literature, these were initially applied to ground EM data by Macnae and Lamontagne (1987) and Nekut (1987). The transformation of survey data to a conductivity-depth cross-section is based upon a receding image of the transmitter loop fitted to the response at each decay time. However, the transformation is approximate because the Earth is assumed to be 1D. Refinements of early CDI schemes are summarised by Wolfgram (1995). It has long been known that interpretation of data collected over 3D and 2D geology using 1D methods can lead to erroneous interpretations (Scott and Fraser, 1973). Various schemes have been devised to minimise artefacts associated with 2D and 3D structures that lead directly to misinterpretation of data, e.g., Walker (1998), Zhdanov and Li (1998). However, despite their promise, such schemes are still very much in their infancy. Through study of the AEM response of several simple models, we sought an understanding of the artefacts associated with 2D structures and how these artefacts affect the response of genuine conductors. NUMERICAL-MODELLING OF AEM DATA We investigate the response of a 2D conductivity distribution excited by a 3D airborne source, the so-called 2.5D problem. This 2.5D problem, which was first studied by Stoyer and Greenfield (1976), allows quite realistic geology to be modelled easily. Although decay rates are slower than for 3D models (Sugeng et al., 1993), the 2.5D approximation is valid for models whose 2D sections are constant over strike lengths of 500 m or more. We used the program Arjuna_Air (Sugeng and Raiche, 1997) for all models in this work. Using the frontal finite-element method (Sugeng et al., 1993), Arjuna_Air describes the Earth using 8-node isoparametric finite elements and solves the frequency-domain problem before transformation to the time domain using techniques described by Raiche (1998). The code's accuracy was tested by direct comparison with 1D solutions, e.g., Ward and Hohmann (1987), and we found good (<2%) agreement between solutions for models with resistivities between 0.01 and 1000 Ω.m when the measurement range was between 0.01 and 100 ms. 1 CRC-AMET School of Earth and Planetary Sciences Macquarie University, NSW 2109 Phone: (02) 9850 9280 Facsimile: (02) 9850 8366 E-mail: David.Annetts@mq.edu.au 2 CRC-AMET School of Earth and Planetary Sciences Macquarie University, NSW 2109 Phone: (02) 9850 9280 Facsimile: (02) 9850 8366 E-mail: Fred.Sugeng@mq.edu.au 3 CRC-AMET School of Earth and Planetary Sciences Macquarie University, NSW 2109 Phone: (02) 9850 9280 Facsimile: (02) 9850 8366 E-mail: James.Macnae@mq.edu.au 4 CRC-AMET School of Earth and Planetary Sciences Macquarie University, NSW 2109 Phone: (02) 9850-9280 Facsimile: (02) 9850 8366 E-mail: Art.Raiche@mq.edu.au Exploration Geophysics (2000) 31, 115-125 115 Exploration Geophysics (2000) Vol 31, Nos. 1 and 2