AN-EUL method for automatic interpretation of potential field data in unexploded ordnances (UXO) detection

This study applied an automatic interpretation method of potential field data called AN-EUL in unexploded ordnance (UXO) prospect, which is indeed a combination of the analytic signal and the Euler deconvolution approaches. The method can be applied for both magnetic and gravity data as well for their gradient surveys based upon the concept of the structural index (SI) of a potential field anomaly, which is related to the geometry of the anomaly sources. With AN-EUL method, both the depth and the approximate geometry (or SI) of the causative sources can be deduced. A realistic model for UXO to be simulated by a simple shape body is a prolate spheroid. The AN-EUL method is applied to synthetic potential field data (gravity and magnetic) by simulation of a collection of causative sources replicating various UXO sizes placed at different depths. In both cases, the estimated depth and the SI of the synthetic UXOs approximately correspond to the synthetic model parameters. The location detection of the causative sources is based upon the Blakely automatic picking algorithm. For both data sets, since the anomaly responses of the small UXOs are affected by noise, the estimated SI is a bit disturbed but the locations correspond to the real ones. The Blakely algorithm also identifies weak anomalies that are due to noise in data; thus, post-processing of the estimated SI of the automatically detected sources may be needed to prevent false alarm sources in UXO exploration. Two field data sets were provided to demonstrate the capability of the applied methods in UXO detection.

Keywords:

Potential Field Data , UXO Detection , AN-EUL Method , Blakely Algorithm , Automatic Interpretation