Combination of horizontal gradient ratio and Euler methods for the interpretation of potential field data

Abstract

The horizontal gradient ratio has been widely used to enhance the linear features of potential field data. I explore a combination of the horizontal gradient ratio and Euler method to interpret gridded potential field data, called HGR-EUL method. A linear equation derived for the Euler equation and expressing the fields as horizontal gradient ratio can be used to estimate the horizontal location and the depth of the source without any priori information about the nature (structural index) of the source. After obtaining the source location parameters, the nature of the source can be determined. The HGR-EUL method is tested on synthetic magnetic anomalies, and the inversion results show that the method can accurately provide the location parameters for noise-free data, and also obtain reasonable results for noise-corrupted data by applying a low pass filter to smooth the data. I also applied the HGR-EUL method to real magnetic data, and the results are compared with results from the standard Euler deconvolution method. The results obtained by the HGR-EUL method show less unjustified variability and are more useful for geologists.