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New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies

A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the for...

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Autor principal: Essa, Khalid S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4294742/
https://www.ncbi.nlm.nih.gov/pubmed/25685472
http://dx.doi.org/10.1016/j.jare.2012.11.006
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author Essa, Khalid S.
author_facet Essa, Khalid S.
author_sort Essa, Khalid S.
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description A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the form f(q) = 0 by defining the anomaly value at the origin and at different points on the profile (N-value). Procedures are also formulated to estimate the depth (z-parameter) and the amplitude coefficient (A-parameter) of the buried structure. The method is simple and rapid for estimating parameters that produced gravity anomalies. This technique is used for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The technique is tested and verified on theoretical models with and without random errors. It is also successfully applied to real data sets from Senegal and India, and the inverted-parameters are in good agreement with the known actual values.
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spelling pubmed-42947422015-02-14 New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies Essa, Khalid S. J Adv Res Original Article A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the form f(q) = 0 by defining the anomaly value at the origin and at different points on the profile (N-value). Procedures are also formulated to estimate the depth (z-parameter) and the amplitude coefficient (A-parameter) of the buried structure. The method is simple and rapid for estimating parameters that produced gravity anomalies. This technique is used for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The technique is tested and verified on theoretical models with and without random errors. It is also successfully applied to real data sets from Senegal and India, and the inverted-parameters are in good agreement with the known actual values. Elsevier 2014-01 2013-01-11 /pmc/articles/PMC4294742/ /pubmed/25685472 http://dx.doi.org/10.1016/j.jare.2012.11.006 Text en © 2014 Cairo University. Production and hosting by Elsevier B.V. All rights reserved. http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
spellingShingle Original Article
Essa, Khalid S.
New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
title New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
title_full New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
title_fullStr New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
title_full_unstemmed New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
title_short New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
title_sort new fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4294742/
https://www.ncbi.nlm.nih.gov/pubmed/25685472
http://dx.doi.org/10.1016/j.jare.2012.11.006
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