A comparative study for the source depth estimation of very low frequency electromagnetic (VLF-EM) signals

A. Ebrahimi*, Narasimman Sundararajan, V. Ramesh Babu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


In general, a quantitative interpretation of geophysical data yields information on the nature of subsurface structures of geologic interest besides depth of the source and the associated physical property contrast. However, all geophysical interpretation invariably incurs an inherent ambiguity including VLF-EM method. Techniques such as Karous-Hjelt (K[sbnd]H) current density, Hilbert transform etc. are in vogue to estimate the depth to the source that are either qualitative or semi quantitative. Here, we present a comparative analysis of the depth derived from VLF-EM signals by different methods over a uranium rich basement fractures of Raigarh District, Chhattisgarh, India. The obtained results are based on techniques that are not very common in VLF-EM data interpretation such as Euler deconvolution (ED), Hartley spectral analysis and analytical signal approach of denoised in-phase component realized by Empirical Ensemble Mode Decomposition (EEMD). The estimated depth from ED and Hartley spectral analysis range 10–62 m and 12–40 m respectively are compared with K[sbnd]H pseudo section, Hilbert transform and drilling depth. Overall, the results of the aforesaid techniques have shown satisfactory comparison wherein the Hilbert transform of EEMD de-noised in-phase component of traverse T1 (35 m), Hartely power spectrum of the principal profile PPQ (40 m) and the radially averaged power spectrum (38.8 m and 40 m) are close to the drilling depth. Therefore, the results obtained by methods presented emphasize that these techniques are equally applicable to VLF-EM signals for estimation of depth to subsurface conductors.

Original languageEnglish
Pages (from-to)174-183
Number of pages10
JournalJournal of Applied Geophysics
Publication statusPublished - Mar 2019


  • Depth estimation
  • Empirical ensemble mode decomposition (EEMD)
  • Euler deconvolution
  • In-phase component
  • Power spectrum
  • Quadrature component

ASJC Scopus subject areas

  • Geophysics


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