Several recent papers have used decay characteristics to predict and map the presence of superparamagnetic (SPM) responses in airborne EM data. Because the most common cause of SPM is irregularly distributed weathering products in the near surface, the majority of SPM anomalies appear as small amplitude responses with short spatial wavelength variations. Even if a significant area of SPM is present, short spatial variations are common. This paper suggests that a combination of small amplitude, characteristic SPM decay shape and short spatial wavelength is unambiguously characteristic of SPM. As a result, there is no need to use two vertically offset receivers to identify SPM with certainty
SPM effects in ground EM data were identified by Lee (1980) and more recently discussed by Barsukov and Fainberg (2001). Recent lowering of the noise levels in AEM systems has led to small amplitude SPM effects being detected on a regular basis. Kratzer et al. (2013) attempted to identify SPM in AEM data using an inverse power-law model, and Sattel and Mutton (2014) showed that the Lee formulation was suited to fitting SPM decays in AEM data with frequency dependent susceptibility ?(?) dependent on two time constants t0 and t1 .
Fig. 1 presents results in standard Lin-Log scales for 4 km of VTEM data from the Mwese survey described by Kratzer and Macnae. The large amplitude feature is a conductor, and ground tests confirmed much SPM materials at surface in the region. To understand the shapes of the small-amplitude, late-time anomalies it is necessary to plot them on a linear scale (Fig.2). Many responses shown by vertical arrows have small peaks of the order of 100 m wide, and slow decays. The conductor has a much wider and larger anomaly as it has significant depth-extent.