oa Development of a helicopter time domain system for bathymetric mapping and seafloor characterisation in shallow water

Time domain airborne electromagnetic (AEM) data acquired from surveys over seawater in Australian coastal waters can be interpreted to obtain seawater depths (Vrbancich and Fullagar, 2007a; Wolfgram and Vrbancich, 2007; Vrbancich, 2009) and to identify the coarse features of bedrock topography (Vrbancich and Fullagar, 2007b; Vrbancich, 2009). A comparison of derived water depths in shallow areas (< 50 m) with known bathymetry has shown that submetre depth accuracies can be achieved but these accuracies are not maintained over the entire survey region. Furthermore, the quantitative interpretation of AEM data using ID inversion methods may require data rescaling (Vrbancich and Fullagar, 2007a; Vrbancich, 2009) and the measured seawater conductivity as a known parameter. The rescaling coefficients in these studies were obtained from the slope and intercept of linear fits between modelled and observed decays at representative sites (control points) with known water depths. These restrictions limit the potential of AEM for accurate bathymetric mapping.

A time domain helicopter AEM system (SeaTEM) is currently being developed for the Defence Science and Technology Organisation for shallow water bathymetric mapping. This system consists of a transmitter and receiver loop assembly mounted on a rigid structure referred to as a "bird" that is towed as a sling load below the helicopter. Instrument stability, calibration (Vrbancich and Fullagar, 2007a; Brodie and Sambridge, 2006; Davis and Macnae, 2008) and the ability to accurately track both the swaying motion (i.e. bird swing) and the altitude of the AEM sensor system over seawater during survey (Davis et al., 2006; Kratzer and Vrbancich, 2007) are issues that need to be addressed in order to develop AEM as a reliable and accurate bathymetry mapping technique. System calibration, self-response, transmitter current waveform, and altimetry were investigated and preliminary findings are reported in this paper.

Before going airborne, the response of SeaTEM instrumentation over seawater was studied in a controlled experiment designed to minimise the effect of bird swing and altimetry errors. For this purpose, the AEM system was floated above seawater using a circular ring, modified from structures used for open-sea fish farming, as the platform. This floating AEM system is referred to as the "sea-ring". Periodic EM measurements were made whilst the sea-ring was being towed at about 2 knots in areas of known water depth. A marine seismic survey provided independent estimates of sediment thickness. Sea-ring data was interpreted to appraise the accuracy of water depths and sediment thickness derived from AEM data and to identify calibration errors.

The AEM bathymetry method also has the potential to provide water depths in the surf zone, so that bathymetry can be used to measure water depths on approaches to beaches (Vrbancich, 2009). The use of LID.AR to estimate the sea surface topography in surf zone areas is under investigation (Vrbancich, unpublished) to support AEM bathymetric mapping. As well as mapping the topography, the LIDAR data also provides accurate altimetry which may be more reliable than using a laser altimeter over seawater.

Airborne and ground EM measurements were conducted over resistive granite to study the system self response. The AEM measurements involved flying over a closed loop of known electrical properties placed on the ground (Davis and Macnae, 2008). The response of the ground loop combined with the flight path can be used to predict the AEM system response. The AEM transmitter current waveform was also measured directly and indirectly from the ground loop data. Apart from the direct measurement of the transmitter current waveform, the results of these findings will be presented separately (Davis et al., 2009).