A filter to detect edge of potential field data based on three-dimensional structural tensors

To detect the edge of potential field is an important task in identifying the horizontal position of geological structure. Although there are many methods based on potential field gradient tensors used to edge detection, the resolved edges remain blurred and inaccurate. This paper defines the structural tensors of a potential field and develops the related edge detectors to outline sources edges. In order to display different-amplitude anomalies simultaneously, we purpose two normalization strategies. When we calculate the new edge detectors, high-order vertical derivatives of potential field computation can increase the noise effect. The new calculation algorithm using horizontal derivatives to calculate vertical derivatives based on Laplace equation is applied to solve this problem. The presented filters tested on a synthetic potential field model show that they can outline the source edges clearly and accurately compared with traditional detectors. For complex situations with positive and negative anomalies, the new methods will not cause extra false edges. At last, we apply these new detectors to the real measured gravity and magnetic data. The results indicate that the new methods have ability to display edges of geological structures clearly and accurately and to discover more subtle information.