Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-03-02T23:01:37Z No. of bitstreams: 1 RafaelaCarreiroDias_DISSERT.pdf: 7493649 bytes, checksum: 18d66dcedc96371bd5f40830e9aec1ba (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-03-04T21:54:12Z (GMT) No. of bitstreams: 1 RafaelaCarreiroDias_DISSERT.pdf: 7493649 bytes, checksum: 18d66dcedc96371bd5f40830e9aec1ba (MD5) / Made available in DSpace on 2016-03-04T21:54:12Z (GMT). No. of bitstreams: 1 RafaelaCarreiroDias_DISSERT.pdf: 7493649 bytes, checksum: 18d66dcedc96371bd5f40830e9aec1ba (MD5) Previous issue date: 2014-03-06 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico - CNPq / O ru?do s?smico tem sido tradicionalmente considerado como uma perturba??o n?o desejada do ambiente que ?contamina? a aquisi??o de dados de terremotos. Mas ao longo da ?ltima d?cada tem sido mostrado que informa??es coerentes sobre a estrutura do subsolo podem ser extra?das a partir de correla??es cruzadas do ru?do s?smico de ambiente. Neste contexto, as regras s?o reversas, sendo os terremotos o que necessitamos excluir dos dados. Os principais causadores do ru?do s?smico de ambiente s?o os microssismos oce?nicos e perturba??es atmosf?ricas. A per?odos menores que 30 s, o espectro do ru?do s?smico de ambiente ? dominado por energia micross?smica. O microssismo ? o sinal s?smico mais cont?nuo da Terra e pode ser classificado como prim?rio (observado na faixa 10-20 s) e secund?rio (observado na faixa 5-10 s). A fun??o de Green do meio de propaga??o entre dois receptores pode ser reconstru?da atrav?s da correla??o cruzada do ru?do s?smico de ambiente registrado simultaneamente nesses dois receptores. A reconstru??o da fun??o de Green ? geralmente proporcional ? por??o de ondas de superf?cie do campo de onda s?smico, j? que a energia micross?smica viaja principalmente como ondas de superf?cie. Neste trabalho, s?o apresentadas 194 fun??es de Green obtidas a partir de correla??es cruzadas de 1 m?s de registro da componente vertical do ru?do s?smico de ambiente para diferentes pares de esta??es s?smicas do Nordeste do Brasil. As correla??es cruzadas di?rias foram empilhadas utilizando a t?cnica n?o linear tf-PWS que real?a sinais coerentes fracos atrav?s da redu??o de ru?do incoerente. As correla??es cruzadas mostram que o sinal emergido ? dominado por ondas Rayleigh nas componentes verticais e que as velocidades de dispers?o podem ser medidas confiavelmente para uma faixa de per?odos entre 5 e 20 s. O estudo inclui tanto esta??es permanentes para monitoramento s?smico, quanto esta??es tempor?rias de experimentos passivos na regi?o, formando uma rede combinada de 33 esta??es separadas por dist?ncias entre 60 e 1311 km, aproximadamente. Estas medidas de velocidades de dispers?o de ondas Rayleigh em seguida s?o usadas na elabora??o de imagens tomogr?ficas da Prov?ncia Borborema do Nordeste do Brasil. As tomografias de ru?do s?smico obtidas aqui permitem mapear satisfatoriamente fei??es estruturais existentes na regi?o. As imagens tomogr?ficas de per?odos mais curtos (~5 s) mostram a estrutura crustal rasa e claramente definem as bacias sedimentares marginais e intracontinentais, bem como as partes de zonas de cisalhamento importantes que atravessam a Prov?ncia Borborema. As imagens tomogr?ficas de per?odos mais longos (10 - 20 s) atingem profundidades da crosta superior e a maior parte das anomalias desaparece. Algumas delas localizada no interior da Prov?ncia Borborema, no entanto, persistem. A evolu??o Cenoz?ica da Prov?ncia Borborema foi marcada por epis?dios de vulcanismo Cenoz?ico e eleva??o, mas nenhuma correla??o ? observada com estas caracter?sticas Cenoz?icas e as anomalias profundas. As anomalias n?o se correlacionam com mapas dispon?veis de fluxo de calor superficial na Prov?nica Borborema, e a origem das anomalias profundas permanece enigm?tica. / Ambient seismic noise has traditionally been considered as an unwanted perturbation in seismic data acquisition that "contaminates" the clean recording of earthquakes. Over the last decade, however, it has been demonstrated that consistent information about the subsurface structure can be extracted from cross-correlation of ambient seismic noise. In this context, the rules are reversed: the ambient seismic noise becomes the desired seismic signal, while earthquakes become the unwanted perturbation that needs to be removed. At periods lower than 30 s, the spectrum of ambient seismic noise is dominated by microseism, which originates from distant atmospheric perturbations over the oceans. The microsseism is the most continuous seismic signal and can be classified as primary ? when observed in the range 10-20 s ? and secondary ? when observed in the range 5-10 s. The Green?s function of the propagating medium between two receivers (seismic stations) can be reconstructed by cross-correlating seismic noise simultaneously recorded at the receivers. The reconstruction of the Green?s function is generally proportional to the surface-wave portion of the seismic wavefield, as microsseismic energy travels mostly as surface-waves. In this work, 194 Green?s functions obtained from stacking of one month of daily cross-correlations of ambient seismic noise recorded in the vertical component of several pairs of broadband seismic stations in Northeast Brazil are presented. The daily cross-correlations were stacked using a timefrequency, phase-weighted scheme that enhances weak coherent signals by reducing incoherent noise. The cross-correlations show that, as expected, the emerged signal is dominated by Rayleigh waves, with dispersion velocities being reliably measured for periods ranging between 5 and 20 s. Both permanent stations from a monitoring seismic network and temporary stations from past passive experiments in the region are considered, resulting in a combined network of 33 stations separated by distances between 60 and 1311 km, approximately. The Rayleigh-wave, dispersion velocity measurements are then used to develop tomographic images of group velocity variation for the Borborema Province of Northeast Brazil. The tomographic maps allow to satisfactorily map buried structural features in the region. At short periods (~5 s) the images reflect shallow crustal structure, clearly delineating intra-continental and marginal sedimentary basins, as well as portions of important shear zones traversing the Borborema Province. At longer periods (10 ? 20 s) the images are sensitive to deeper structure in the upper crust, and most of the shallower anomalies fade away. Interestingly, some of them do persist. The deep anomalies do not correlate with either the location of Cenozoic volcanism and uplift - which marked the evolution of the Borborema Province in the Cenozoic - or available maps of surface heat-flow, and the origin of the deep anomalies remains enigmatic.