Novel Second-Order Derivative-Based Filters for Edge and Ridge/Valley Detection in Geophysical Data

Derivative-based high-pass filters of various types are commonly applied to potential field data to reveal subtle or hard-to-see structures in the quest for mineral exploration. One approach is to exploit the fact that data have an amplitude and phase component in the space domain. In the past, this has been used to produce first-order derivative-based enhanced datasets with minimal noise issues. The work is extended here to second-order derivative-based filters, which are useful in enhancing not just edges but also ridges and valleys in data. The filters compare favourably with existing second-order derivative-based filters that were applied to gravity and magnetic datasets from South Africa.