We investigate the properties of EM signals in several different response-parameter domains to identify calibration errors in helicopter electromagnetic (HEM) data. In particular, we define a dimensionless response parameter α, derived from frequency-domain data, that is numerically identical to the historic wire-loop response parameter, and is closely related to the thin-sheet and half-space response parameters. The arctangent of α is the phase ϕ of the secondary field. We further define a dimensionless amplitude response parameter β, calculated as the ratio between inductive limits estimated from the data and from system geometry. The inductive limit calculated from geometry provides an initial altitude correction to the data amplitudes. Additional data corrections further correct phase effects and altimeter variations. The amplitude and phase errors in calibration become independent differences between the data and the fitted model in the ϕβ domain. This investigation was undertaken in the response-parameter domain rather than in the data domain, allowing the analysis to be independent of absolute values of conductivity and system frequencies. Statistical analysis in the ϕβ domain of recently acquired data suggests that amplitude calibration errors in HEM data may cause fitted models to have systematic depth errors of 1 to 2 m for near-surface conductors; variable altitude measurement errors are about 1.5 m over seawater.

We aim to develop a quantitative method for recalibration of historic helicopter electromagnetic data sets. Recent research has shown that frequency-domain helicopter electromagnetic data collected over a conductive half-space such as calm seawater can be used to correct system calibration errors. However, most historic surveys consist only of data collected over land, where the conductive half-space assumption is rarely justified. We estimate the required recalibration parameters by analyzing systematic misfits in the inversion of statistically chosen measures of historic data. Our method requires the identification, within the survey area, of a zone of conductive responses that are reasonably uniform. From this zone, a set of altitude-corrected median responses are estimated. These are inverted using geologically specifiedconstraints to obtain a best-fit layered earth model. Systematic inconsistencies between the median measured altitude and the inverted depth to surface are attributed to altitude error. Remaining frequency-dependent fitting errors are assumed to be the calibration errors. We tested the method with partial success on helicopter electromagnetic data sets collected over uniform deep sediments where seawater data were also available and two different inland surveys over multiple lithologies in one general area. At high frequencies, our method works reliably. Recalibration of low-frequency data is not possible if the area used as a reference consists of moderate or poor conductors. In this case, data amplitudes are small and are greatly affected by imperfect drift and magnetic susceptibility corrections. Historic helicopter electromagnetic data may require amplitude rescaling up to 20%–30%, with phase shifts of up to 3°.