Digital filters applications on aeromagnetic data for identification of hidden objects

Abstract

The hidden objects are located, as sixteen objects (anomalies) on the reduction to magnetic pole data (RTP). The follow-up and identification of these objects by applying several digital filters, as upwarding continuation at different level, then the horizontal derivative (HD) and vertical derivative (VD). Accordingly, the edge detection filter techniques are dependent on the tilt derivative (horizontal, vertical derivatives) and the tilt angle. This study shows closing to the basic dykes (shallow anomalies) that imprinted in the RTP map and the upward continuation maps at shallow levels. The residual features are mostly starting to disappear gradually in the upward continuation maps at intermediate and deeper levels. The last upwarding maps illustrate the penetrated roots of these bodies to deep levels (deep anomalies). The advanced filter technique of edge detection is the enhanced total horizontal derivative of the tilt angle (ETHDR). This study delineates and compares the hidden objects by applying the different filter techniques, as the analytical signal (AS), first vertical derivative (FVD), total horizontal derivative (THDR), tilt angle (TA), horizontal tilt angle (TDX), and ETHDR. The applied derivative-based filters, as ETHDR, produce more detailed results for the shallower and deeper magnetized structures. The compared filter results such as TA, TDX, and ETHDR give sharp edges of the magnetized sources (hidden objects). Quantitatively, the determined depths have been evaluated, using the 2D modeling algorithm. The depths and relief of the basement surface across eight profiles are defined, and the depths and shapes of the hidden objects are outlined. Meanwhile, magnetic susceptibility contrasts of the hidden objects are varied with different expanding shapes and subsurface depths.