1887
Volume 73, Issue 6
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Radiomagnetotellurics (RMTs) is an efficient frequency‐domain electromagnetic technique for mapping subsurface electrical resistivity, particularly suited for near‐surface investigations. This method utilizes commonly available civil and military radio transmitters, broadcasting between 10 kHz and 1 MHz, as sources to measure electric and magnetic field responses at the surface. Modern RMT receiver systems comprise five components (two electrical antennas and three magnetic coils), allowing for the estimation of the full impedance tensor and the tipper transfer function for the vertical magnetic field. In this study, RMT data were acquired to investigate the shallow structure of the Himalayan Frontal Thrust (HFT) fault in the Sub‐Himalayan region around Uttarakhand, India. Data were collected at 312 stations along eight profiles over an area of roughly 500 m × 70 m. The dense station distribution enables a 3D inversion of the dataset in the extended frequency range of up to 1 MHz. The observed data were processed using scalar as well as tensor estimations to obtain full impedances and tipper transfer function. We integrated scalar‐estimated data from zones with an approximately 2D conductivity distribution in the full‐tensor dataset. This approach ensured robust 3D modelling during the initial RMT inversion performed with the ModEM algorithm. To date, a joint 3D interpretation of RMT full impedance tensor and tipper transfer function has not yet been reported. Furthermore, the near‐surface manifestations of the HFT have not previously been explored by RMT. The derived 3D model from combined scalar, tensor and tipper data reveals a conductivity contrast zone that aligns well with the HFT fault outcrop and complementary geological information. The derived geo‐electrical structure recovers the local sediment thickness and shallow fault inclination.

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2025-07-24
2026-02-13
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  • Article Type: Research Article
Keyword(s): 3D inversion; electromagnetics; Himalaya; radiomagnetotellurics; tensor processing; tipper

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