Levelling of helicopter-borne frequency-domain electromagnetic data |
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| Authors: | Bernhard Siemon |
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| Institution: | 1. Dept of Crop and Soil Science, The University of Georgia, United States of America;2. Odum School of Ecology, The University of Georgia, United States of America;3. Nicholas School of the Environment, Duke University, United States of America;4. Warnell School of Forestry and Natural Resources, The University of Georgia, United States of America;1. College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China;2. Graduate School of the Department of Water Resources, Inner-Mongolia 010020, China;1. School of the Environment, Flinders University, GPO Box 5100, Adelaide, SA 5001, Australia;2. National Centre for Groundwater Research and Training, Flinders University, GPO Box 5100, Adelaide, SA 5001, Australia |
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| Abstract: | For about three decades helicopter-borne electromagnetic (HEM) measurements have been used to reveal the resistivity distribution of the upper one hundred metres of the earth's subsurface. HEM systems record secondary fields, which are 3–6 orders of magnitude smaller than the transmitted primary fields. As both the primary fields and the secondary fields are present at the receivers, well-designed bucking coils are often used to reduce the primary fields at the receivers to a minimum. Remaining parts of the primary fields, the zero levels, are generally corrected by subtracting field values recorded at high altitudes (standard zero levelling) or estimated from resistivities of neighbouring lines or from resistivity maps (advanced zero levelling). These zero-levelling techniques enable the correction for long-term, quasi-linear instrumental drift. Short-term variations caused by temperature changes due to altitude variations, however, cannot be completely corrected by this procedure resulting in stripe patterns on thematic maps.Statistical methods and/or 2-D filter techniques called statistical levelling (tie-line levelling) and empirical levelling (microlevelling), respectively, used to correct stripe patterns in airborne geophysical data sets are, in general, not directly applicable to HEM data. Because HEM data levelling faces the problem that the parameter affected by zero-level errors, the secondary field, differs from the parameter generally levelled, the apparent resistivity. Furthermore, the dependency of the secondary field on both the resistivity of the subsurface and the sensor altitude is strongly nonlinear.A reasonable compromise is to microlevel both half-space parameters: apparent resistivity and apparent depth, followed by a recalculation of the secondary field components based on the half-space parameters levelled. Advantages and disadvantages of the diverse levelling techniques are discussed using a HEM data set obtained in a hilly region along the Saale River between the cities of Saalfeld and Jena in central Germany. It turns out from a comparison of apparent resistivity and apparent depth maps derived from levelled HEM data that manually advanced zero levelling of major level errors and automatic microlevelling of remaining minor level errors yield the best results. |
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