Edge enhancement of potential field data using an enhanced tilt angle

Abstract

We present an edge-detection technique for the enhancement of potential field data, which is based on the tilt angle of the first order vertical derivative of the total horizontal gradient. The technique can be performed using three steps, as follows: first, we calculate the total horizontal gradient of the potential fields, which is stable and effective in determining the horizontal locations; second, we calculate the first order vertical derivative of the total horizontal gradient to increase the vertical-resolution on the basis of the determined the horizontal locations; finally, we display the tilt angle of the first order vertical derivative of the total horizontal gradient tending to balance the amplitude responses from both shallow and deep sources. This technique is designed to reflect the complex distributions of multiple sources with different depths and extents. The effectiveness of our method is demonstrated by synthetic data. The results indicate that the new filter generates more subtle detail for superimposed sources, compared with other edge detection filters. The method is also applied to field surveyed data from the Saskatoon area of Canada, and the results are helpful for qualitative interpretation.