Cargando…

Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm

The inefficiencies and uncertainties surrounding solutions from existing inversion methods have necessitated investigation for more efficient techniques for the inversion of ill-posed magnetic problems. In this study, the Social Spider Optimization (SSO) algorithm has been modified, adopted and succ...

Descripción completa

Detalles Bibliográficos
Autores principales: Ben, Ubong C., Akpan, Anthony E., Urang, Job Gideon, Akaerue, Emmanuel I., Obianwu, Victor I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914121/
https://www.ncbi.nlm.nih.gov/pubmed/35284665
http://dx.doi.org/10.1016/j.heliyon.2022.e09027
_version_ 1784667634422251520
author Ben, Ubong C.
Akpan, Anthony E.
Urang, Job Gideon
Akaerue, Emmanuel I.
Obianwu, Victor I.
author_facet Ben, Ubong C.
Akpan, Anthony E.
Urang, Job Gideon
Akaerue, Emmanuel I.
Obianwu, Victor I.
author_sort Ben, Ubong C.
collection PubMed
description The inefficiencies and uncertainties surrounding solutions from existing inversion methods have necessitated investigation for more efficient techniques for the inversion of ill-posed magnetic problems. In this study, the Social Spider Optimization (SSO) algorithm has been modified, adopted and successfully used in modelling physical characteristics of magnetic anomalies originating from simple-shaped geologic structures. The study, aimed at testing the capacity and efficiency of the SSO algorithm to model magnetic data of varying complexity, was successfully conducted on both synthetic data with varying levels of noise and real field data obtained from mining fields in Senegal and Egypt. To assess the mathematical nature of the inverse problem considered, error energy maps were produced for each model parameter pairs in the synthetic examples. These maps enabled the pre-assessment of the resolvability model parameter for the ill-posed problem. In addition, uncertainty analysis aimed at providing insight to the reliability of the obtained solutions was carried out using the Metropolis–Hastings (M–H) sampling algorithm. Results show that the procedure converges fast and generates accurate results even when confronted with constrained multi-parameter non-linear inversion problems. Its outstanding converging speed and accuracy of the results reveal it as an excellent procedure for overcoming agelong problems of local optimal solutions associated with pre-existing algorithms. The consistency of the results with actual values affirms the efficacy of the new procedure which is pioneering in geophysical literature. It is therefore a stable and efficient tool for performing geophysical data inversion and is therefore recommended for use in inverting geophysical data with higher complexities like seismic reflection and gravity data, that require many corrections to be performed before reliable geological interpretations can be made.
format Online
Article
Text
id pubmed-8914121
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-89141212022-03-12 Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm Ben, Ubong C. Akpan, Anthony E. Urang, Job Gideon Akaerue, Emmanuel I. Obianwu, Victor I. Heliyon Research Article The inefficiencies and uncertainties surrounding solutions from existing inversion methods have necessitated investigation for more efficient techniques for the inversion of ill-posed magnetic problems. In this study, the Social Spider Optimization (SSO) algorithm has been modified, adopted and successfully used in modelling physical characteristics of magnetic anomalies originating from simple-shaped geologic structures. The study, aimed at testing the capacity and efficiency of the SSO algorithm to model magnetic data of varying complexity, was successfully conducted on both synthetic data with varying levels of noise and real field data obtained from mining fields in Senegal and Egypt. To assess the mathematical nature of the inverse problem considered, error energy maps were produced for each model parameter pairs in the synthetic examples. These maps enabled the pre-assessment of the resolvability model parameter for the ill-posed problem. In addition, uncertainty analysis aimed at providing insight to the reliability of the obtained solutions was carried out using the Metropolis–Hastings (M–H) sampling algorithm. Results show that the procedure converges fast and generates accurate results even when confronted with constrained multi-parameter non-linear inversion problems. Its outstanding converging speed and accuracy of the results reveal it as an excellent procedure for overcoming agelong problems of local optimal solutions associated with pre-existing algorithms. The consistency of the results with actual values affirms the efficacy of the new procedure which is pioneering in geophysical literature. It is therefore a stable and efficient tool for performing geophysical data inversion and is therefore recommended for use in inverting geophysical data with higher complexities like seismic reflection and gravity data, that require many corrections to be performed before reliable geological interpretations can be made. Elsevier 2022-03-02 /pmc/articles/PMC8914121/ /pubmed/35284665 http://dx.doi.org/10.1016/j.heliyon.2022.e09027 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Ben, Ubong C.
Akpan, Anthony E.
Urang, Job Gideon
Akaerue, Emmanuel I.
Obianwu, Victor I.
Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm
title Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm
title_full Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm
title_fullStr Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm
title_full_unstemmed Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm
title_short Novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (SSO) algorithm
title_sort novel methodology for the geophysical interpretation of magnetic anomalies due to simple geometrical bodies using social spider optimization (sso) algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914121/
https://www.ncbi.nlm.nih.gov/pubmed/35284665
http://dx.doi.org/10.1016/j.heliyon.2022.e09027
work_keys_str_mv AT benubongc novelmethodologyforthegeophysicalinterpretationofmagneticanomaliesduetosimplegeometricalbodiesusingsocialspideroptimizationssoalgorithm
AT akpananthonye novelmethodologyforthegeophysicalinterpretationofmagneticanomaliesduetosimplegeometricalbodiesusingsocialspideroptimizationssoalgorithm
AT urangjobgideon novelmethodologyforthegeophysicalinterpretationofmagneticanomaliesduetosimplegeometricalbodiesusingsocialspideroptimizationssoalgorithm
AT akaerueemmanueli novelmethodologyforthegeophysicalinterpretationofmagneticanomaliesduetosimplegeometricalbodiesusingsocialspideroptimizationssoalgorithm
AT obianwuvictori novelmethodologyforthegeophysicalinterpretationofmagneticanomaliesduetosimplegeometricalbodiesusingsocialspideroptimizationssoalgorithm