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Decomposing the electromagnetic response of magnetic dipoles to determine the geometric parameters of a dipole conductor

A novel automatic data interpretation algorithm is presented for modelling airborne electromagnetic (AEM) data acquired over resistive environments, using a single-component (vertical) transmitter, where the position and orientation of a dipole conductor is allowed to vary in three dimensions. The algorithm assumes that the magnetic fields produced from compact vortex currents are expressed as a linear combinations of the fields arising from dipoles in the subsurface oriented parallel to the [1, 0, 0], [0, 1, 0], and [0, 0, 1], unit vectors. In this manner, AEM responses can be represented as 12 terms. The relative size of each term in the decomposition can be used to determine geometrical information about the orientation of the subsurface conductivity structure. The geometrical parameters of the dipole (location, depth, dip, strike) are estimated using a combination of a look-up table and a matrix inverted in a least-squares sense. Tests on 703 synthetic models show that the algorithm is capable of extracting most of the correct geometrical parameters of a dipole conductor when three-component receiver data is included in the interpretation procedure. The algorithm is unstable when the target is perfectly horizontal, as the strike is undefined. Ambiguities may occur in predicting the orientation of the dipole conductor if y-component data is excluded from the analysis. Application of our approach to an anomaly on line 15 of the Reid Mahaffy test site yields geometrical parameters in reasonable agreement with previous authors. However, our algorithm provides additional information on the strike and offset from the traverse line of the conductor. Disparities in the values of predicted dip and depth are within the range of numerical precision. The index of fit was better when strike and offset were included in the interpretation procedure. Tests on the data from line 15701 of the Chibougamau MEGATEM survey shows that the algorithm is applicable to situations where three-component AEM data is available.