When airborne electromagnetic (AEM) data is acquired as a streamed or time-series data set, the great redundancy in the data favours compression as a first step in processing. Traditional data compression schemes are time windowing and spatial averaging. An alternative, more efficient data compression scheme is to transform time or frequency domain data to time-constant tau space, which has the effect of removing the waveform dependence of the AEM response. When there are many local anomalies and a variable background, the next stage of rapid processing is to transform the response to a conductivity-depth image (CDI) to facilitate geological interpretation of the background response. Use of the full time range of recorded data, particularly the inclusion of on-time data, improves the stability of the CDI process. The final AEM data processing step for mineral exploration is to assess the likelihood that any local anomaly corresponds to a desired economic target. This step involves the extraction of target geometry and conductivity information from the AEM data. The only economically feasible route at the present time is to parameterise both the data (using inductive and resistive limits) and the model to allow inversion of the local anomalies. A fit to one or two plate-like conductors can be achieved in seconds; fits to a block-like body take minutes on a fast PC. A significant research challenge remains to speed up and stabilise this process.

A variety of signal processing techniques can be used to minimize the effects of noise on linear, wideband, electromagnetic (EM) systems operating in the time-domain. All systems use repetitive waveforms with polarity reversal in alternate half-cycles. Exponential averaging or digital integration (stacking) is employed to increase signal-to-noise (S/N) ratios by limiting the noise acceptance to narrow frequency bands centered on odd harmonics of the repetition frequency, the width of the acceptance bands being inversely proportional to stacking time. For certain types of nonstationary noise (e.g., occasional transients) or coherent noise (e.g., powerlines) it is possible to increase S/N ratios above those obtained by simple stacking for an equal time by use of techniques such as pruning, tapered stacking or randomized stacking. With some system waveforms and when the noise spectrum is not 'white', use of pre-emphasis filtering in the transmitter and a corresponding de-emphasis filter in the receiver may significantly improve the input S/N ratio before stacking. Specific applications of the various techniques are discussed with reference to one particular time-domain EM system, the UTEM 3 system. By their use, improvements in S/N ratio of as much as 6 to 1 have been regularly achieved without any increase in transmitter power, depending on the nature of the local noise.

An 'imaged' conductivity section of a layered earth can be obtained by simple transformation of step-response electromagnetic data measured in the quasi-static zone. This method of data transformation is presented as an alternative to conventional apparent conductivity transformations. At each delay time, the variation of the step response as a function of geometry (transmitter and receiver location) is transformed to an equivalent reference depth h, which can be related to the depth of electromagnetic field diffusion. The behavior of h as a function of delay time is nearly independent of the source-receiver geometry. The slowness dt/dh divided by the magnetic permeability is almost exactly proportional to the cumulative conductance measured from the surface down to a depth h. Thus we can estimate an apparent conductivity, which we call the 'imaged conductivity,' at depth to be d 2 t/mu 0 dh 2 .The cost of this transformation is a fraction of the cost of conventional data inversion, and it does not require an a priori constraint on the number of parameters used in the inversion. The empirically developed technique was used successfully to process UTEM field data measured over a quasi-layered earth.

A major impediment in the path toward airborne induced polarization (IP) is an effective method to quantify data from inductive sources, such as those used in airborne electromagnetic systems. We modeled inductive IP using a combination of Warburg and exponential decay models as a basis for fitting electromagnetic data from ground time-domain electromagnetic (TEM) and airborne versatile TEM (VTEM) surveys. Observed decays were deconvolved into electromagnetic and IP constituents by constrained least-squares fitting of basis functions modified to account for transmitter waveforms. The method was confirmed through synthetic modeling of 2D and 3D structures, and when applied to ground TEM or airborne TEM data, obtained an estimate of apparent chargeability at each station or fiducial. In the case of a VTEM survey in Africa, the apparent chargeabilities mapped graphitic sediments and provided spatially consistent indications of clay concentrations. A limitation on this airborne IP for airborne applications is motion noise, which places a lower limit on usable base frequency and begins to significantly affect the signal at the later delay times, when IP effects are most visible.