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Imageamento e modelagem digital com GPR em microbialitos da Fazenda Arrecife, Chapada Diamantina (BA), NE do Brasil

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Previous issue date: 2017-08-07 / O trabalho envolve o imageamento e modelagem digital de uma col?nia microbial?tica neoproterozoica do afloramento da Fazenda Arrecife (BA), com o uso do m?todo Ground Penetrating Radar (GPR) e a aplica??o de atributos matem?ticos. Concomitantemente, foi realizado o levantamento de se??es colunares e a aquisi??o de perfis radioativos, permitindo a caracteriza??o das f?cies sedimentares. Foram tamb?m realizados estudos petrogr?ficos e an?lises qu?micas (MEV/SED e FRX) para identificar a composi??o dos n?veis escuros (estilol?ticos), que geram reflex?es nos radargramas. O atributo ?Amplitude Instant?nea? real?ou a col?nia de microbialitos (baixa amplitude), pois exibe um padr?o de assinatura GPR distinto. O atributo de ?Energia? apresentou resultados semelhantes ao de ?Amplitude Instant?nea?, proporcionando uma melhor visualiza??o da lamina??o interna do microbialito colunar. J? o atributo de ?Similaridade? real?ou o limite da col?nia com os dep?sitos tempest?ticos. A combina??o ?Tra?o de Hilbert com Energia? mostrou um realce mais significativo do limite de crescimento da col?nia microbial?tica do que o atributo de ?Energia? isolado. J? o atributo ?Tra?o de Hilbert com Similaridade? real?ou a estrutura interna da col?nia microbial?tica. Foram descritas as f?cies microbial?ticas (MCme, MCm e MCma) e f?cies tempest?tica (Cahm). O estudo petrogr?fico indicou a presen?a de minerais como limonita e/ou siderita, o que corrobora com os resultados das an?lises qu?micas. As an?lises qu?micas com MEV/SED e FRX mostram que no n?vel estilol?tico ocorre maiores valores de Fe (11,9%), justificando assim os fortes refletores observados nas se??es GPR, que s?o resultado do contraste eletromagn?tico entre o meio (?calc?rio = 6,55) e o os n?veis estilol?ticos (?ferro= 14,2). Para a modelagem digital, foi elaborado um s?lido 3D que representa adequadamente a col?nia microbial?tica. A metodologia abordada neste trabalho, envolvendo a aplica??o de atributos aos dados GPR, permitiu real?ar caracter?sticas do microbialito que foram pouco observadas no dado original. Portanto, pode ser utilizada em outros contextos geol?gicos semelhantes (aflorantes ou n?o-aflorantes). / This thesis involves the digital imaging and modeling of a neoproterozoic microbialitic colony in the Fazenda Arrecife (BA) outcrop, using the Ground Penetrating Radar (GPR) method and the application of mathematical attributes. Concomitantly, columnar sections and radioactive profiles acquisition were carried out, allowing the characterization of the sedimentary facies. Petrographic studies and chemical analysis (SEM/EDS and XRF) were used to identify the composition of the stylolithic levels that generate reflections in the GPR sections. The "Instantaneous Amplitude" attribute highlighted a microbialite community (low amplitude), which displays different signature pattern. The "Energy" attribute showed a similar result comparing to the "Instantaneous Amplitude". Nevertheless, this attribute provided a better visualization of the internal lamination of the columnar microbialite. The "Similarity" attribute emphasized the community boundary. The "Hilbert Trace/Energy" combination showed significant enhancement of the microbial growth boundaries compared to the "Energy" attribute. The attribute "Hilbert Trace/Similarity" highlighted the internal structure of the microbial community. The described facies were designated as microbialitic facies (MCme, MCm and MCma) and tempestite facies (Cahm). Minerals, such as limonite and/or siderite, were identified by the petrographic study, which corroborates with the chemical analysis results. The chemical analysis shows high Fe values to the stylolithic level, which causes the reflections observed in the GPR sections, due to the electromagnetic contrast between the microbialite (? = 6.55) and the stylolithic levels (? = 14.2). The generated 3D solid properly represents a microbial community. The attribute application to GPR data allowed to highlight the microbialitic features not observed in the original data. Therefore, this application can be used in similar geologic contexts.

Identiferoai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/24847
Date07 August 2017
CreatorsLima, Rebeca Seabra de
Contributors13893700382, Castro, David Lopes de, 40623742420, Neumann, Virg?nio Henrique, 24494631434, Lima Filho, Francisco Pinheiro
PublisherPROGRAMA DE P?S-GRADUA??O EM GEODIN?MICA E GEOF?SICA, UFRN, Brasil
Source SetsIBICT Brazilian ETDs
LanguagePortuguese
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis
Sourcereponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN
Rightsinfo:eu-repo/semantics/openAccess

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