Fast approximate inversion of SkyTem airborne electromagnetic data

Abstract

Transient electromagnetic (TEM) soundings have become one of the standard methods of environmental geophysics (Fittermann and Stewart, 1986; Buselli et al., 1990; Hoekstra and Blohm, 1990; Christensen and Sørensen, 1998; Auken et al., 2006; Lane and Pracilio, 2000). Over the past decades, airborne TEM methods have found widespread use in hydrogeophysical investigations, making it possible to cover large areas in a cost-effective way. Several helicopterborne TEM systems have been developed and they now represent the most up-to-date method of airborne hydrogeophysical investigations, collecting 100,000s of data sets. We present a fast approximate method for one-dimensional inversion of time domain electromagnetic data and apply it to SkyTEM helicopterborne data from the Toolibin Lake area of West Australia. The method is based on fast approximate forward computation of transient electromagnetic step responses and their derivatives with respect to the model parameters of a 1D model. The inversion is carried out with multi-layer models in a state-of-the-art formulation of a least-squares iterative inversion scheme including explicit formulation of the model regularization through a model covariance matrix. The method is 50 times faster than conventional inversion for a layered earth model and produces model sections of concatenated 1D models and contoured maps of mean conductivity in elevation intervals almost indistinguishable from those of conventional inversion. To ensure lateral smoothness of the model sections and to avoid spurious artifacts in the mean conductivity maps, the Lateral Parameter Correlation method is applied to the results of the individual inversion models. In this way, well determined parameters are allowed to influence the more poorly determined parameters in the survey area. Applied to the SkyTEM Toolibin data set, the inversion produces model sections and conductivity maps that reveal the distribution of conductivity in the area and thereby the distribution of salinity. This information is crucial for any remediation effort aimed at alleviating the salinity problems. The results are in accordance with previous results from other investigators.