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Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data

Subsurface source boundary identification is a major step in the interpretation of potential field anomalies in geophysical exploration. We investigated the behavior of wavelet space entropy over the boundaries of 2D potential field source edges. We tested the robustness of the method for complex so...

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Detalles Bibliográficos
Autores principales: Dwivedi, Divyanshu, Chamoli, Ashutosh, Rana, Sandip Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955358/
https://www.ncbi.nlm.nih.gov/pubmed/36832608
http://dx.doi.org/10.3390/e25020240
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author Dwivedi, Divyanshu
Chamoli, Ashutosh
Rana, Sandip Kumar
author_facet Dwivedi, Divyanshu
Chamoli, Ashutosh
Rana, Sandip Kumar
author_sort Dwivedi, Divyanshu
collection PubMed
description Subsurface source boundary identification is a major step in the interpretation of potential field anomalies in geophysical exploration. We investigated the behavior of wavelet space entropy over the boundaries of 2D potential field source edges. We tested the robustness of the method for complex source geometries with distinct source parameters of prismatic bodies. We further validated the behavior with two datasets by delineating the edges of (i) the magnetic anomalies due to the popular Bishop model and (ii) the gravity anomalies of the Delhi fold belt region, India. The results showed prominent signatures for the geological boundaries. Our findings indicate sharp changes in the wavelet space entropy values corresponding to the source edges. The effectiveness of wavelet space entropy was compared with the established edge detection techniques. The findings can help with a variety of geophysical source characterization problems.
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spelling pubmed-99553582023-02-25 Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data Dwivedi, Divyanshu Chamoli, Ashutosh Rana, Sandip Kumar Entropy (Basel) Article Subsurface source boundary identification is a major step in the interpretation of potential field anomalies in geophysical exploration. We investigated the behavior of wavelet space entropy over the boundaries of 2D potential field source edges. We tested the robustness of the method for complex source geometries with distinct source parameters of prismatic bodies. We further validated the behavior with two datasets by delineating the edges of (i) the magnetic anomalies due to the popular Bishop model and (ii) the gravity anomalies of the Delhi fold belt region, India. The results showed prominent signatures for the geological boundaries. Our findings indicate sharp changes in the wavelet space entropy values corresponding to the source edges. The effectiveness of wavelet space entropy was compared with the established edge detection techniques. The findings can help with a variety of geophysical source characterization problems. MDPI 2023-01-28 /pmc/articles/PMC9955358/ /pubmed/36832608 http://dx.doi.org/10.3390/e25020240 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dwivedi, Divyanshu
Chamoli, Ashutosh
Rana, Sandip Kumar
Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data
title Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data
title_full Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data
title_fullStr Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data
title_full_unstemmed Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data
title_short Wavelet Entropy: A New Tool for Edge Detection of Potential Field Data
title_sort wavelet entropy: a new tool for edge detection of potential field data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955358/
https://www.ncbi.nlm.nih.gov/pubmed/36832608
http://dx.doi.org/10.3390/e25020240
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AT ranasandipkumar waveletentropyanewtoolforedgedetectionofpotentialfielddata