Unexploded ordnance location and identification using borehole magnetometry

It is estimated that 10% of war-time bombs did not explode and can be found either lying on the ground or buried at depths of up to 20 m depending on the soil type. These unexploded bombs also known as ordnance pose a real danger to construction workers and properties. Ground-surface-based detection methods are unable to detect objects at such depths due to the rapidly diminishing nature of the anomalous field and interference from metal debris on the ground surface. A borehole magnetometer equipped with a drilling system can penetrate to the depths of interest and collect high-resolution field data. However, conventional inversion techniques are incapable of handling one-dimensional borehole data due to the insufficient number of available data points. To overcome these difficulties, a borehole detection method is proposed that has an inversion algorithm specifically developed to deal with the high non-uniqueness of the borehole data. It has the advantages of a fast convergence and maximisation of information extracted from individual borehole measurements. This method is more reliable than traditional methods since it examines all the possibilities by taking a number of estimations. The information from each individual borehole is fully interpreted, allowing suggestions to be made for the positioning of the next drilling point allowing the minimisation of the number of holes required to obtain a definative solution. This results in a reduction in both hazard levels and cost. A method is proposed based on the recovered information that allows the identification and discrimination of unexploded ordnance from other objects in the search environment, such as steel pipes and barrels. It is not sensitive to interference in the data once the moment signature is recovered. The results obtained from a test site are extremely promising and demonstrate the proposed techniques capability to handle real-world inversion problems despite having only a small number of available data points.