Demonstration Results

The methods developed were the two-dipole iterative residual algorithm and a simultaneous two-dipole fit algorithm the demonstrators named “double happiness.” On synthetic magnetometer data, the double happiness algorithm performed well, and better than the iterative residual method. On synthetic electromagnetic data, the double happiness algorithm performed better than the iterative residual method, but differences in the assumed sensor (EM61MkI versus EM61MkII) made the direct comparison slightly ambiguous.

On overlapping signature data collected at the Blossom Point, Maryland test facility with an EM61MkII, the iterative residual method performed reasonably well for the 4 cases of target pairs separated by 0.5m, but there was not enough data with real horizontal separations to adequately evaluate the algorithm.

On the synthetic data, both algorithms had some difficulty separating two dipoles that are close in horizontal separation, since the signature from the compact targets will appear like a single dipole. Fortunately, this situation is less important in practice than the situation in which a weaker target lies some distance from a stronger target, but the two signatures overlap and the weaker target is not detected. In such situations, traditional methods will locate the stronger target, but its excavation may miss the weaker one. In this case, the double happiness algorithm may perform more than adequately.