NHF as an Edge Detector of Potential Field Data and Its Application in the Yili Basin

Abstract

Edge enhancement is a frequently used transformation of potential field data. Its goal is to sharpen the position of the subsurface structures. Here we propose a new method to enhance the edges of the sources causing the potential anomalies called normalized Harris filter (NHF), which is based on the Harris filter and amplitude balance. Three synthetic data sets are used to evaluate the performance of the proposed approach. The presented approach provides a better estimation of the sources’ edges when compared to the other methods. The proposed method is robust to noisy data and can avoid the generation of artificial edges, thereby reducing the ambiguity of interpretation. The testing on real data set from the Yili basin in Northwestern China demonstrates that the new approach highlights several anomalies not shown in the geological map or other methods. The proposed approach also shows the advantages of gradually enhancing the edges of the deep-seated structure. The results demonstrate that the proposed approach may be a better detector in qualitatively determining the edges of sources causing potential field data.