Use este identificador para citar ou linkar para este item: http://www.repositorio.ufop.br/jspui/handle/123456789/8153
Título: Electrical imaging of impact structures.
Autor(es): Tong, C. H.
Elis, Vagner Roberto
Lana, Cristiano de Carvalho
Marangoni, Yára Regina
Palavras-chave: Resistivity
Impact crater
Geophysical inversion
Araguainha
Data do documento: 2012
Referência: TONG, C. H. et al. Electrical imaging of impact structures. Surveys in Geophysics, v. 33, p. 861–868, 2012. Disponível em: <https://link.springer.com/article/10.1007/s10712-012-9178-y>. Acesso em: 20 de jun. 2017.
Resumo: Electrical imaging provides important subsurface information for the construction of hypervelocity impact models. We here provide an overview and evaluation of the current electrical imaging methods used in impact cratering studies. Although apparent resistivity models are commonly used in the geoelectrical imaging of impact structures, the reliability of these models has not hitherto been determined. In order to assess these imaging approaches in impact cratering, we investigate for the first time the discrepancies between the apparent resistivity and true resistivity models of an impact structure. To this end, we present (1) a new true resistivity model of the Araguainha impact structure in central Brazil by applying L2-norm inversion to previously published data, (2) apparent resistivity model of the impact structure, and (3) models obtained from different stages of the iterative tomographic inversions. Our results show that changes in vertical resistivity gradient are significantly better defined in the true resistivity models than in the apparent resistivity model. On the basis of these results, we outline a new approach that true resistivity models can be effectively assessed by applying both L1- and L2-norm inversion schemes together with the monitoring of intermediate models from iterative inversion. The results of our study highlight the importance of tomographic inversion of resistivity data in impact cratering studies, and they provide a data modeling framework and foundation for cost-effective subsurface imaging of impact structures in the future.
URI: http://www.repositorio.ufop.br/handle/123456789/8153
Link para o artigo: https://link.springer.com/article/10.1007/s10712-012-9178-y
DOI: https://doi.org/10.1007/s10712-012-9178-y
ISSN: 1573-0956
Aparece nas coleções:DEGEO - Artigos publicados em periódicos

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