Open Access


Download data is not yet available.


In the potential field inverse problems, accurate determination of the location for the anomaly sources and their properties played an important role. For geomagnetic anomalies of adjacent sources, they always superimpose upon each other not only in the spatial domain but also in the frequency domain, making the identification of these sources significantly problematic. In this paper, a new mother wavelet for effective analysis the properties of the close potential field sources was used. By theoretical modeling, using the wavelet transform modulus maxima (WTMM) method, we set up a correlative function between the scale parameter and geomagnetic source depth. Moreover, a scale normalization on the wavelet coefficients was introduced to enhancethe resolution for the separation of these sources in the scalograms, thereby determining their depth. After verifying the reliability of the proposed method on the modeling data, we have analysed the geomagnetic data in the Mekong delta. The results of this interpretation were consistency with previously published ones, furthermore, the level of resolution for this technique was quite coincidental with other methods using different geological data.

Author's Affiliation
Article Details

Issue: Vol 1 No 6 (2017)
Page No.: 273-286
Published: Dec 8, 2018
Section: Original Research

 Copyright Info

Creative Commons License

Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Duong, T., Duong, D., & Nguyen, T. (2018). Identification of magnetic anomalies of adjacent sourses using the wavelet transform modulus maxima and scale normalization. Science and Technology Development Journal - Natural Sciences, 1(6), 273-286.

 Cited by

Article level Metrics by Paperbuzz/Impactstory
Article level Metrics by Altmetrics

 Article Statistics
HTML = 97 times
Download PDF   = 89 times
Total   = 89 times