A self-consistent response function estimator for airborne natural source EM processing

SUMMARY Airborne natural source electromagnetics (EM) provide spatially densely gridded, frequency-dependent intersite transfer function estimates referring airborne vertical and horizontal magnetic field data to the horizontal components of a ground site. Common processing schemes for airborne natural source EM data are conceptually based on approaches developed for ground-based magnetotelluric sounding curve estimation and yield statistically independent transfer function estimates for selected times windows and separately for each component of the airborne recording. However, the magnetic field is spatially smooth and, moreover, its components are mutually dependent in space. Here, we propose to exploit spatial potential field relations directly in the processing workflow to refine transfer functions. The self-consistent response function estimator is applied after a first statistical estimation of transfer functions and supports the determination of a spatially smooth and self-consistent set of vertical and horizontal magnetic transfer functions that reflects physical constraints. Self-consistency is enforced by fitting sources distributed within an equivalent sheet to a preliminary set of transfer function estimates determined on a statistical basis. Smoothness is controlled by the depth to the equivalent sources. Once estimated, the distribution of vertical and horizontal magnetic transfer functions can be predicted from the equivalent sheet at any point in the air half-space. Additionally, the scheme allows for the identification of anomalous parts of the horizontal fields at the ground site. The procedure is demonstrated on a large-scale field data set from Gobabis (Namibia). We observe that transfer functions derived by using the equivalent source layer interpolator improve processing results when compared to purely statistically determined transfer function averages.