Processing and Inversion of Magnetic Gradient Tensor Data for Uxo Applications

Abstract

We present a set of techniques for processing and inverting multi-component magnetic gradient data for UXO detection and discrimination. A magnetic gradiometer for the UXO application, developed jointly by US Geological Survey and Colorado School of Mines, measures the full gradient tensor of a magnetic field. In contrast to total-field intensity measurements, gradient data have the advantage that they are less affected by common-mode noise and may carry more useful information about subsurface targets. Multiple tensor components also enable the extraction of a coherent common signal to further increase the signal-to-noise ratio. The increased data quality opens new avenues for developing novel approaches to UXO detection and discrimination. We have examined two different processing methods based on the inherent relationship among the multiple tensor components, and we have developed an inversion algorithm for recovering dipole and quadrupole source parameters from tensor data. We outline these algorithms and illustrate the advantages of gradient data over total-field measurements.