Application of improved balancing filters to edge identification of potential field data

Edge identification is an indispensable task in the interpretation of potential field data. The existing methods have the disadvantages that the recognized edges are diffuse and the edges of the deeper sources are blurred. We presented enhanced balancing filters that can effectively overcome the disadvantages existing in the previous filters. The improved filters use the various combinations of different order derivatives to recognize the source edges, and we introduced a stable algorithm of the high-order vertical derivatives. The enhanced balancing filters are demonstrated on synthetic potential field data, which can display the edges of the shallow and deep bodies simultaneously, and can display the edges of the sources more precisely and clearly compared to the other filters. At last, we applied the enhanced balancing filters to measured potential field data, which can divide the horizontal locations of the faults and the boundaries of different strata easily based on the results, and can discover more subtle details.