Join us for this presentation at the Canadian Exploration Geophysical Society's (KEGS) annual Symposium. The theme of the Symposium this year is Geophysics and the Environment and the talk will be presented by Tom Furuya of Acorn SI.

Click here to register for the Symposium and download the event program.

Darren Mortimer, Geosoft Inc.
Nick Valleau, Geosoft Inc.
Dean Keiswetter, Acorn SI
Tom Furuya, Acorn SI


During unexploded ordnance (UXO) or munition clean-up projects, most items excavated are not UXO, but are harmless scrap metal.  Historically, target selection has been based on magnetic or electromagnetic (EM) anomaly amplitudes, footprints, and shapes - features of the data rather than of the source object itself.

New sensors have been developed to facilitate reliable classification of UXO. These time-domain electromagnetic (TEM) systems have three key improvements from previous EM sensors used for UXO work:

  • multiple transmitter and receiver coils;
  • finer sampling of the time decay;
  • longer sampling periods.

Classification depends on calculating model parameters that relate to intrinsic physical features of targets rather than to external features such as location and orientation.  Forward modelling and inversion yield polarizabilities and decay parameters, as well as accurate location and depth of the buried object. Polarizabilities relate to the object’s intrinsic size and shape, whereas decays relate to the material properties and wall thickness.  UXO are typically cylindrical, therefore they have one strong (primary) polarizability, and two weaker but equal polarizabilities (secondary & tertiary).  This distinguishing characteristic of cylindrical objects immediately identifies a target as being a potential UXO.

The classification process then determines the likelihood that an item is a UXO.  Polarizability curves are mathematically compared to a signature library of known UXO to find matches.  To find munitions that are not in the library, all the target polarizability data from a survey area are also analyzed to find “clusters” of similar objects.  Such objects are then evaluated to establish their nature.

With these new advanced EM sensors and processes, reliable classification of suspected UXO targets using geophysical survey data is now possible, enabling millions of dollars in savings on cleanup projects.

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