Synthetic models reveal inductive systems struggle with noise, suggesting galvanic sources enhance deep exploration accuracy.
Summary Recently, semi-airborne transient electromagnetic (TEM) systems have gained attention in geophysical investigations due to their ability for fast mapping and minimal ground access requirement. These systems consist of a ground-based transmitter source and an inductive receiver coil, carried by an uncrewed aerial vehicle. This study investigates how transmitter source selection in field-based semi-airborne TEM systems affects model parameter uncertainty, using synthetic subsurface models. The simulated dB/dt responses highlight distinct signal characteristics between the galvanic-based system (herein galvanic source) and the inductive-based system (herein inductive source), with differences observed across varying subsurface conditions. An analysis of four synthetic 3-layer models highlights that the inductive-based system resolves shallow conductors better at short offsets, whereas the galvanic-based system is better at resolving parameters for deeper targets at large offsets. Both systems, however, face challenges in accurately resolving resistive targets embedded between conductors, highlighting the need for strategic selection of the transmitter source. The galvanic-based system consistently achieves a higher signal-to-noise ratio (SNR), particularly at large offsets, making it better suited for deep exploration. In contrast, the inductive-based system exhibits lower SNR, higher noise susceptibility, and sign-changing dB/dt responses at increasing offsets adding complexity to data processing and interpretation. Despite these limitations, inductive-based systems enable earlier time measurements with signal magnitudes at short offsets comparable to galvanic-based, due to shorter current turn-off times. In this analysis we have used two system setups utilizing inductive and galvanic sources that reflect commonly used systems, but obviously, assumptions regarding transmitter characteristics such as type, size, waveform, and current amplitude, will influence the results when examining details more closely.
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Almpanis et al. (2025) studied this question.
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