An improved algorithm for the Euler deconvolution of potential field data

Abstract

Euler deconvolution (Thomson 1982, Reid et al. 1990) is a commonly used semiautomatic interpretation method for magnetic and gravity data. It can be used to indicate locations and depths of anomalous bodies, indicating regions of interest that can be followed up by detailed modeling. Recent work has suggested the usefulness of applying Euler deconvolution to the vertical gradient of the potential field data (Ravat et al. 2002, Hsu 2002). Because the vertical gradient anomaly is narrower than that of the field itself, its use provides improved horizontal resolution of the solutions. However the greater the order of the gradient used, the greater the problems with noise become (because the vertical derivative operator is a high-pass filter). This paper suggests a way around this problem for the first vertical derivative and uses synthetic models of magnetic and gravity data to show the benefits of the approach.