Articles | Volume 15, issue 1
https://doi.org/10.5194/gi-15-183-2026
https://doi.org/10.5194/gi-15-183-2026
Research article
 | 
21 May 2026
Research article |  | 21 May 2026

Enhanced removal of very low frequency and low frequency radio noise from transient electromagnetic data with modeling and adaptive filtering

Michel Hardenberg and Jakob Juul Larsen

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This preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).
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Cited articles

Asif, M. R., Maurya, P. K., Foged, N., Larsen, J. J., Auken, E., and Christiansen, A. V.: Automated Transient Electromagnetic Data Processing for Ground-Based and Airborne Systems by a Deep Learning Expert System, IEEE T. Geosci. Remote, 60, 5919814, https://doi.org/10.1109/TGRS.2022.3202304, 2022. a
Auken, E., Foged, N., Larsen, J. J., Lassen, K. V. T., Maurya, P. K., Dath, S. M., and Eiskjær, T. T.: tTEM – A towed transient electromagnetic system for detailed 3D imaging of the top 70 m of the subsurface, Geophysics, 84, E13–E22, https://doi.org/10.1190/geo2018-0355.1, 2019. a
Behroozmand, A. A., Auken, E., and Knight, R.: Assessment of Managed Aquifer Recharge Sites Using a New Geophysical Imaging Method, Vadose Zone J., 18, 1–13, https://doi.org/10.2136/vzj2018.10.0184, 2019. a
Chandra, S., Auken, E., Maurya, P. K., Ahmed, S., and Verma, S. K.: Large Scale Mapping of Fractures and Groundwater Pathways in Crystalline Hardrock By AEM, Scientific Reports, 9, 398, https://doi.org/10.1038/s41598-018-36153-1, 2019. a
Chen, K., Zhang, J., Xue, G., Huang, H., Chen, W., Hao, J., and Yue, Y.: Feasibility of Monitoring Hydraulic Connections between Aquifers Using Time-lapse TEM: A Case History in Inner Mongolia, China, J. Environ. Eng. Geoph., 24, 361–372, https://doi.org/10.2113/JEEG24.3.361, 2019. a
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Short summary
Transient electromagnetics (TEM) is traditionally used for mapping, but new use-cases are emerging. For example, a stationary TEM instrument can gather time-lapse data. By observing dynamic changes of the subsurface resistivity model, it is possible to track changes in groundwater levels. However, the changes are minuscule and data sets with very high signal-to-noise ratios are therefore crucial. We demonstrate a method for suppressing noise from a specific type of radio noise.
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