This thesis develops and explores two methodologies to assess earthquake ground shaking in southwestern British Columbia based on 1D soil layering and 3D basin structure. To assess site response based on soil layering, microtremor array measurements were conducted at two sites of contrasting geology to estimate Rayleigh-wave dispersion curves. A Bayesian inversion algorithm is developed to invert the dispersion data for the shear-wave velocity (VS) profile together with quantitative uncertainty estimates, accounting rigorously for data error covariance and model parameterization selection. The recovered VS profiles are assessed for reliability by comparison with invasive VS measurements at each site with excellent agreement. Probabilistic site response analysis is conducted based on a sample of VS profiles drawn from the posterior probability density of the microtremor inversion. The quantitative uncertainty analysis shows that the rapid and inexpensive microtremor array method provides sufficient resolution of soil layering for practical characterization of earthquake ground motion. To assess the effects of 3D Georgia basin structure on long-period (> 2 s) ground motion for large scenario earthquakes, numerical 3D finite difference modelling of viscoelastic wave propagation is applied. Both deep (> 40 km) subducting Juan de Fuca plate and crustal (5 km) North America plate earthquakes are simulated in locations congruent with known seismicity. Simulations are calibrated by comparing synthetic waveforms with 36 selected strong- and weak-motion seismograms of the 2001 MW 6.8 Nisqually earthquake. The ratio between predicted peak ground motions in models with and without Georgia basin sediments is applied as a quantitative measure of basin amplification. Steep edges in the upper 1 km of the northwest and southeast extents of the basin are coincident with the appearance of surface waves. Focussing of north-to-northeast propagating surface waves by shallow (< 1 km) basin structure increases ground motion in a localized region of southern Greater Vancouver. This effect occurs for both types of earthquakes located south-southwest of Vancouver at distances greater than ~80 km. The predicted shaking level is increased up to 17 times and the duration of moderate shaking (> 3.4 cm/s) is up to 16 times longer due to the 3D Georgia basin structure. / Graduate

Title: Influence of velocity model uncertainty in earthquake source inversions Author: Miroslav Halló Department: Department of Geophysics Supervisor: doc. RNDr. František Gallovič, Ph.D., Department of Geophysics Abstract: Earthquake ground motions originate from rupture processes on faults in Earth. Constraints on earthquake source models are important for better un- derstanding of earthquake physics and for assessment of seismic hazard. The source models are inferred from observed waveforms by inverse modeling, which is subject to uncertainty. For large tectonic earthquakes the major source of un- certainty is an imprecise knowledge of crustal velocity model. The research topic of this Thesis is the influence of the velocity model uncertainty on the inferred source models. We perform Monte-Carlo simulations of Green's functions (GFs) in randomly perturbed velocity models to reveal the effects of the imprecise veloc- ity model on the synthetic waveforms. Based on the knowledge gained, we derive closed-form formulas for approximate covariance functions to obtain fast and effective characterization of the GFs' uncertainty. We demonstrate that approxi- mate covariances capture correctly the GF variability as obtained by the Monte- Carlo simulations. The proposed approximate covariance functions are...

[pt] Esta tese propõe uma metodologia de estimativa de pressão de poros em rochasreservatório através dos atributos sísmicos velocidade compressional V(p) e velocidade cisalhante V(s). Na metodologia, os atributos são encarados como observações realizadas sobre um sistema físico, cujo comportamento depende de um determinado número de grandezas não observáveis, dentre as quais a pressão de poros é apenas uma delas. Para estimar a pressão de poros, adota-se uma abordagem Bayesiana de inversão. Através de uma função de verossimilhança, estabelecida através de um modelo de física de rochas calibrável para a região, e do teorema de Bayes, combina- se as informações pré-existentes sobre os parâmetros de rocha, fluido e estado de tensões com os atributos sísmicos observados, inferindo probabilisticamente a pressão de poros. Devido a não linearidade do problema e ao interesse de se realizar uma rigorosa análise de incertezas, um algoritmo baseado em simulações de Monte Carlo (um caso especial do algoritmo de Metropolis- Hastings) é utilizado para realizar a inversão. Exemplos de aplicação da metodologia proposta são simulados em reservatórios criados sinteticamente. Através dos exemplos, demonstra-se que o sucesso da previsão de pressão de poros depende da combinação de diferentes fatores, como o grau de conhecimento prévio sobre os parâmetros de rocha e fluido, a sensibilidade da rocha perante a variação de pressões diferenciais e a qualidade dos atributos sísmicos. Visto que os métodos existentes para previsão de pressão de poros utilizam somente o atributo V(p) , a contribuição do atributo V(s) na previsão é avaliada. Em um cenário de rochas pouco consolidadas (ou em areias), demonstra-se que o atributo V(s) pode contribuir significativamente na previsão, mesmo apresentando grandes incertezas associadas. Já para um cenário de rochas consolidadas, demonstra-se que as incertezas associadas às pressões previstas são maiores, e que a contribuição do atributo V(s) na previsão não é tão significativa quanto nos casos de rochas pouco consolidadas. / [en] This work proposes a method for pore pressure prediction in reservoir rocks through compressional- and shear-velocity data (seismic attributes). In the method, the attributes are considered observations of a physic system, which behavior depends on a several not-observable parameters, where the pore pressure is only one of these parameters. To estimate the pore pressure, a Bayesian inversion approach is adopted. Through the use of a likelihood function, settled through a calibrated rock physics model, and through the Bayes theorem, the a priori information about the not-observable parameters (fluid and rock parameters and stress state) is combined with the seismic attributes, inferring probabilistically the pore pressure. Due the non-linearity of the problem, and due the uncertainties analysis demanding, an algorithm based on Monte Carlo simulations (a special case of the Metropolis- Hastings algorithm) is used to solve the inverse problem. The application of the proposed method is simulated through some synthetic examples. It is shown that a successfully pore pressure prediction in reservoir rocks depends on a set of factors, as how sensitive are the rock velocities to pore pressure changes, the a priori information about rock and fluid parameters and the uncertainties associates to the seismic attributes. Since the current methods for pore pressure prediction use exclusively the attribute compressional velocity V(p), the contribution of the attribute shear velocity V(s) on prediction is evaluated. In a poorly consolidated rock scenario (or in sands), the V(s) data, even with great uncertainties associated, can significantly contribute to a better pore pressure prediction. In a consolidated rock scenario, the uncertainties associated to pore pressure estimates are higher, and the s V data does not contribute to pore pressure prediction as it contributes in a poorly consolidated rock scenario.

Les satellites glacés de Jupiter sont d'un grand intérêt scientifique dans la recherche d'habitabilité au sein de notre système solaire. Elles abritent probablement toutes trois des océans d'eau liquide sous leur croûte glacée. Leurs surfaces présentent différents stades d’évolution – celle de Callisto est très ancienne et entièrement recouverte de cratères, celle de Ganymede est un mélange de terrains sombres et cratérisés et de plaines claires et plus jeunes et la surface d’Europa est la plus jeune et présente des signes d’activité récente. Cette thèse porte sur la photométrie, c’est à dire l’étude de l’énergie lumineuse réfléchie par une surface, en fonction des géométries d’éclairement et d’observation. Les études photométriques permettent de déterminer l’état physique et la microtexture des surfaces (porosité, structure interne, forme des grains, rugosité, transparence…). Une bonne connaissance photométrique est également d'une importance cruciale dans la correction des jeux de données pour toute étude cartographique ou spectroscopique ainsi que pour les futures missions de cette décennie : Europa Clipper de la NASA et JUpiter ICy Moons Explorer de l’ESA.Deux types d’information sont nécessaires pour réaliser une étude photométrique : des données de réflectance et des données géométriques (conditions d’illumination et d'observation). Pour obtenir les premières, nous avons utilisé et calibré des images de missions spatiales passées - Voyager, New Horizons et Galileo. Pour obtenir les secondes, nous avons développé des outils permettant de corriger les métadonnées de ces images (ex : la position et l'orientation des sondes) afin d’obtenir des informations géométriques précises. Nous avons, d’autre part, développé un outil d’inversion pour estimer les paramètres photométriques de Hapke sur des régions d’Europa, Ganymede et Callisto sur l’ensemble du jeu de données en un seul calcul. Enfin, nous discutons des liens possibles entre les paramètres photométriques estimés, la microtexture de la surface et les processus endogènes/exogènes mis en jeu. / Jupiter's icy moons are of great interest in the search for habitability in our Solar System. They probably all harbor liquid water ocean underneath their icy crust. Their surfaces present different stages of evolution – Callisto is heavily cratered and the oldest, Ganymede shows a combination of dark cratered terrain and younger bright plains and Europa’s surface is the youngest with signs of recent and maybe current activity. This work focuses on photometry, i.e. the study of the light scattered by a surface in relation to the illumination and observation geometry. Photometric studies give us insight on the physical state and microtexture of the surface (compaction, internal structure, shape, roughness, transparency…). A good photometric knowledge is also of crucial importance in the correction of datasets for any mapping or spectroscopic study as well as for the future missions of this decade – NASA’s Europa Clipper and ESA’s JUpiter ICy moons Explorer.Two pieces of information are necessary to conduct a photometric study – reflectance data and geometric information (illumination, viewing conditions). For the former, we have used and calibrated images from past space missions – Voyager, New Horizons and Galileo. For the latter, we have developed tools to correct these images metadata (e.g. spacecraft position and orientation) to derive precise geometric information. Moreover, we have developed a Bayesian inversion tool to estimate Hapke’s photometric parameters on regions of Europa, Ganymede and Callisto. We estimate all parameters on our entire dataset at once. Finally, we discuss the possible links between the photometric parameters, the surface microtexture and endogenic/exogenic processes.