Balanced horizontal derivative of potential field data to recognize the edges and estimate location parameters of the source

Abstract

Edge detection is a common task in the interpretation of potential field data, and many edge detection filters are presented to accomplish this task, which are the functions composed by the first-order horizontal derivative and vertical derivative of potential field data, but we find that the edges recognized by the existing edge detection filters are bigger than the true edges. In this paper, we present the balanced horizontal derivative (BHD) edge detection filter, which uses the ratio of the first-order horizontal derivative to the second-order horizontal derivative to recognize the edges of the source, and the recognized edges by the BHD edge detection filter are more correct and are more insensitive to noise. We derive a linear equation based on the derivatives of the BHD to estimate the depth of the source, and we also present a normalized total horizontal derivative (NTHD) method to image the location of the source. We demonstrate the presented methods on synthetic potential field data, and the results show that the presented methods can provide the edges and location parameters of the sources correctly, and the BHD filter can display the edges more clearly and correctly. At last, we apply the presented methods to real potential field data, and the inversion results computed by the presented methods are in accord with the geology information.