The simultaneous application of Euler deconvolution to magnetic and gravity datasets

Euler deconvolution is a commonly used semi-automatic interpretation method for potential field data. There are many variations of the method available, in that it can be applied to the Hilbert transforms and/or the derivatives of the data in different ways. Some methods solve for the source type (the structural index) while others require it to be a priori specified. The source location is obtained by using the overdetermined least-squares method to solve a set of equations based on a moving window of data points. It has been applied to both gravity and magnetic data frequently in the past, both individually and together. However in the latter case the datasets require normalisation due to the different amplitudes of the gravity and magnetic datasets. Normalisation is problematic because it does not work well for profiles that contain multiple anomalies with different amplitudes. In addition it is strongly affected by outliers in the data. A new approach is presented here that does not require any a priori normalisation. In addition, the method can be used with gravity and magnetic datasets that were acquired at different altitudes, such as ground gravity data with airborne magnetic data. The method is demonstrated using geophysical data from Southern Africa..