1887

Abstract

Summary

We may use the Continuous Wavelet transform to analyse data at different scales and positions. In this work we apply Spector and Grant’s method to estimate the depths to the top and bottom of the magnetic anomalies causative sources by calculating the power spectrum using the 2D Morlet wavelet at different central wavenumbers. A 3-D scalogram is obtained by averaging the CWT power spectrum over rotation angles, so forming a Fan. The scalogram is locally analyzed to select the suitable scales for depth estimation. The method was tested by synthetic data of a two superimposed prism and a real magnetic anomaly of Macomer from the aeromagnetic anomaly map of Sardinia, Italy. The results are in accordance with the true parameters and known information of the sources.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202520242
2025-09-07
2026-02-14
Loading full text...

Full text loading...

References

  1. Antoine, J. P. and Murenzi, R. [1996] Two-dimensional directional wavelets and the scale-angle representation. Signal processing, 52(3), 259–281.
    [Google Scholar]
  2. Bhattacharyya, B. K. [1966] A method for computing the total magnetization vector and the dimensions of a rectangular block-shaped body from magnetic anomalies. Geophysics, 31(1), 74–96.
    [Google Scholar]
  3. Fedi, M. and Mastro, S. [2018] Bounded-region wavelet spectrum: A new tool for depth estimation of gravity and magnetic data. SEG Technical Program Expanded Abstracts, 1425–1429.
    [Google Scholar]
  4. Fedi, M., Quarta, T. and De Santis, A. [1997] Inherent power-law behavior of magnetic field power spectra from a Spector and Grant ensemble. Geophysics, 62(4), 1143–1150.
    [Google Scholar]
  5. Fedi, M., and Rapolla, A. [1997] Space-frequency analysis and reduction of potential field ambiguity. Annals of Geophysics, 40(5), 1189–1200.
    [Google Scholar]
  6. Galdeano, A. and Ciminale, M. [1987] Aeromagnetic evidence for the rotation of Sardinia (Mediterranean Sea): comparison with the paleomagnetic measurements. Earth and planetary science letters, 82(1–2), 193–205.
    [Google Scholar]
  7. Gaudreau, É., Audet, P. and Schneider, D. A. [2019] Mapping Curie depth across western Canada from a wavelet analysis of magnetic anomaly data. Journal of Geophysical Research: Solid Earth, 124(5), 4365–4385.
    [Google Scholar]
  8. Kelemework, Y., Fedi, M. and Milano, M. [2021] A review of spectral analysis of magnetic data for depth estimation. Geophysics, 86(6), J33–J58.
    [Google Scholar]
  9. Kirby, J. F. [2005] Which wavelet best reproduces the Fourier power spectrum?. Computers & geosciences, 31(7), 846–864.
    [Google Scholar]
  10. Naidu, PS. [1968] Spectrum of the potential field due to randomly distributed source. Geophysics, 33, 337–345.
    [Google Scholar]
  11. Sobh, M., Gerhards, C., Fadel, I. Götze, H. J. [2021] Mapping the thermal structure of Southern Africa from Curie depth estimates based on wavelet analysis of magnetic data with uncertainties. Geochemistry, Geophysics, Geosystems, 22(11), e2021GC010041.
    [Google Scholar]
  12. Spector, A. and Grant, F. S. [1970] Statistical models for interpretating aeromagnetic data. Geophysics, 35, 293–302.
    [Google Scholar]
/content/papers/10.3997/2214-4609.202520242
Loading
/content/papers/10.3997/2214-4609.202520242
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error