Helicopter time-domain electromagnetic (HTEM) surveying has historically been used for mineral exploration, but over the past decade it has started to be used in environmental assessments and geologic and hydrologic mapping. Such surveying is a cost-effective means of rapidly acquiring densely spaced data over large regions. At the same time, the quality of HTEM data can suffer from various inaccuracies. We have developed an effective strategy for processing and inverting a commercial HTEM data set affected by uncertainties and systematic errors. The delivered data included early time gates contaminated by transmitter currents, noise in late time gates, and amplitude shifts between adjacent flights that appeared as artificial lineations in maps of the data and horizontal slices extracted from inversion models. Multiple processing steps were required to address these issues. Contaminated early time gates and noisy late time gates were semi-automatically identified on the basis of slope changes in the dB/dt transients and eliminated on a record-by-record basis. Timing errors between the transmitter and receiver electronics and inaccuracies in absolute amplitudes were corrected after calibrating selected HTEM data against data simulated from accurate ground-based TEM measurements. After editing and calibration, application of a quasi-3D spatially constrained inversion scheme significantly reduced the artificial lineations. Residual lineations were effectively eliminated after incorporating the transmitter and receiver altitudes and line-to-line amplitude factors in the inversion process. The final inverted model was very different from that generated from the original data provided by the contractor. As examples, the average resistivity of the thick surface layer decreased from ~1800 to ~30 Ωm, the depths to the layer boundaries were reduced by 15%–23%, and the artificial lineations were practically eliminated. Our processing and inversion strategy is entirely general, such that with minor system-specific modifications it could be applied to any HTEM data set, including those recorded many years ago.


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