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.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-08-09T23:00:00Z No. of bitstreams: 1 VirginieD'hour_TESE.pdf: 8753386 bytes, checksum: 2e3e6a55a73239c9eeac2c8def85eb39 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-08-13T00:23:12Z (GMT) No. of bitstreams: 1 VirginieD'hour_TESE.pdf: 8753386 bytes, checksum: 2e3e6a55a73239c9eeac2c8def85eb39 (MD5) / Made available in DSpace on 2016-08-13T00:23:12Z (GMT). No. of bitstreams: 1 VirginieD'hour_TESE.pdf: 8753386 bytes, checksum: 2e3e6a55a73239c9eeac2c8def85eb39 (MD5) Previous issue date: 2015-09-01 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / Nesta tese s?o apresentados e discutidos os resultados de correla??o do ru?do s?smico em dois contextos: regi?o intraplaca e Dorsal Meso-oce?nica. O m?todo de interferometria de cauda de onda (coda wave interferometry?CWI) tamb?m foi utilizado para os dados da regi?o intraplaca. A correla??o do ru?do permite recuperar a fun??o de Green emp?rica entre dois receptores , como se uma das esta??es atuasse como uma fonte (virtual). Esta t?cnica ?amplamente utilizado em sismologia para a imagem do subsolo e para monitorar mudan?as estruturais associadas principalmente com erup??es vulc?nicas e terremotos grandes (mb > 6.0). No estudo da regi?o intraplaca, fomos capazes de detectar mudan?as estruturais localizadas relacionadas com esta pequena sequ?ncia de terremotos, cujo evento principal ? de mR 3.7, no Nordeste do Brasil. N?s tamb?m mostramos que a normaliza??o de 1-bit de e o branqueamento spectral provoca perdas de detalhes na forma de onda e que a auto- correla??o de fase, que ? pouco sens?vel ? amplitude , parece ser mais sens?vel e robusta para a nossa an?lise. A an?lise de 6 meses de dados usando correla??es cruzadas detecta claramente altera??es do meio logo ap?s do evento principal, enquanto que as auto- correla??es essencialmente detectam altera??es ap?s 1 m?s. Estas mudan?as na correla??o cruzada e na auto-correla??o podem serexplicadas pela redistribui??o da press?o do fluido ocasionadas mudan?as hidromec?nicas e novos caminhos preferenciais para difus?o de press?o e fuidos , devido a terramotos que ocorrem mais tarde. No estudo da Dorsal Meso-oce?nica, investigamos as mudan?as estruturais associadas a um terremoto de mb 4,9 aolongo da falha transformante de S?o Paulo. Os dados foram registrados por a ?nica esta??o s?smica localizada a menos de 200 km da Dorsal Meso-oce?nica. Os resultados da auto-correla??o de fase por um per?odo de 5 meses, mostram uma forte mudan?a de meio co-s?smica seguido por uma recupera??o p?s-s?smica relativamente r?pida. Esta mudan?a do meio provavelmente est? relacionada aos danos causados pelo terremoto de mb 4.9. O processo de cicatriza??o (enchimento das novas fissuras) que durou 60 dias pode ser decomposto em duas fases, uma recupera??o r?pida na fase p?s-s?smica (de 70% em ~ 30 dias) precoce e uma recupera??o relativamente lenta depois (de 30% em ~ 30 dias) No estudo de interferometria de cauda de onda, monitoramos mudan?as temporais da subsuperf?cie causada pela sequ?ncia de pequenos terremotos intraplaca mencionado anteriormente. O m?todo foi validado com dados sint?ticos. Fomos capazes de detectar uma mudan?a da fonte de 2.5% e uma redu??o de 15% da quantidade dos espalhadores. A partir dos dados reais, observamos uma r?pida diminui??o da correla??o da cauda da onda ap?s do evento s?smico mR 3.7. Isso indica uma mudan?a r?pida do subsolo na regi?o da falha induzida pelo terremoto. / This thesis presents and discusses the results of ambient seismic noise correlation for two different environments: intraplate and Mid-Atlantic Ridge. The coda wave interferometry method has also been tested for the intraplate data. Ambient noise correlation is a method that allows to retrieve the structural response between two receivers from ambient noise records, as if one of the station was a virtual source. It has been largely used in seismology to image the subsurface and to monitor structural changes associated mostly with volcanic eruptions and large earthquakes. In the intraplate study, we were able to detect localized structural changes related to a small earthquake swarm, which main event is mR 3.7, North-East of Brazil. We also showed that the 1-bit normalization and spectral whitening result on the loss of waveform details and that the phase auto-correlation, which is amplitude unbiased, seems to be more sensitive and robust for our analysis of a small earthquake swarm. The analysis of 6 months of data using cross-correlations detect clear medium changes soon after the main event while the auto-correlations detect changes essentially after 1 month. It could be explained by fluid pressure redistribution which can be initiated by hydromechanical changes and opened path ways to shallower depth levels due to later occurring earthquakes. In the Mid-Atlantic Ridge study, we investigate structural changes associated with a mb 4.9 earthquake in the region of the Saint Paul transform fault. The data have been recorded by a single broadband seismic station located at less than 200 km from the Mid-Atlantic ridge. The results of the phase auto-correlation for a 5-month period, show a strong co-seismic medium change followed by a relatively fast post-seismic recovery. This medium change is likely related to the damages caused by the earthquake?s ground shaking. The healing process (filling of the new cracks) that lasted 60 days can be decomposed in two phases, a fast recovery (70% in ~30 days) in the early post-seismic stage and a relatively slow recovery later (30% in ~30 days). In the coda wave interferometry study, we monitor temporal changes of the subsurface caused by the small intraplate earthquake swarm mentioned previously. The method was first validated with synthetics data. We were able to detect a change of 2.5% in the source position and a 15% decrease of the scatterers? amount. Then, from the real data, we observed a rapid decorrelation of the seismic coda after the mR 3.7 seismic event. This indicates a rapid change of the subsurface in the fault?s region induced by the earthquake.