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The Brunswick No. 6 area, which is located in the Bathurst Mining Camp, New Brunswick, Canada, is the focus of this thesis. Almost a decade ago, in order to improve the understanding of the crustal structures and explore for new mineral deposits at depth, three 2D seismic profiles totaling about 30 km and 3D seismic data covering an area of about 38 km2 were acquired from the study area. Petrophysical properties including compressional-wave velocity and density were also measured in two deep boreholes in the area. These data were recovered and reanalyzed, and the improved seismic images interpreted as the main part of this PhD thesis. A prestack DMO and poststack migration algorithm was considered for processing both 2D and 3D data. Processing of 2D data revealed shallow and deep reflections, which correlate well with surface geology. Steeply-dipping reflections, some of which could host mineral deposits, were imaged down to a depth of 6-7 km. Processing of 3D data showed similar results to the processed 2D profiles. Nevertheless, the non-orthogonal nature of the 3D survey, combined with irregular distribution of offsets, azimuths and trace midpoints, caused a severe acquisition footprint masking reflections in the DMO-corrected unmigrated stacked cube. An FK-dip filter in the wavenumber domain was designed to reduce the effects of the acquisition footprint. To better understand wave propagation and scattering effects, calculated acoustic impedance log from the available borehole data was used to estimate vertical scale length using a von Karman autocorrelation function. 2D synthetic models representative of heterogeneity in the area were generated accounting for the estimated scale length. Numerical modeling was used to study the scattering effects on the synthetic models, where some predefined targets were superimposed in the provided 2D heterogeneous medium. The effects of variable source frequency, longer horizontal scale length and petrophysical fluctuations of heterogeneous medium were also investigated. The modeling results indicate that, in the presence of large horizontal, but small vertical scale lengths (structural anisotropy), the identification of mineral deposits is possible in the unmigrated stacked sections, but can be challenging in the migrated sections.

Cette thèse contribue à la modélisation de la variabilité spatiale de la résistance à la traction des structures en béton, à différentes échelles, et son influence sur la fissuration du béton. En particulier, une loi d'effet d'échelle et des champs aléatoires sont utilisés à l'aide de deux approches:D'une part, une approche analytique probabiliste de la méthode Weakest Linkand Localization (WL2) est proposée. Cette méthode estime la distribution de la résistance à la traction, à différentes échelles, en tenant compte des redistributions des contraintes autour du point le plus faible. Cela dépend d'une longueur d'échelle, dont l'identification est discutée. Cette longueur d'échelle explique le caractère aléatoire de la résistance à la traction du béton.D'autre part, une autre contribution de cette thèse est le développement d'une méthode Élément Fini Stochastique (EFS), utilisée pour modéliser l'effet d'échelle et la variabilité spatiale de la résistance à la traction. La méthode consiste d'abord à définir un champ aléatoire, en utilisant la résistance à la traction réduite estimée à partir de l'approche analytique de WL2. Ensuite, des réalisations de champs aléatoires autocorrélées discrétisées sont générées. En outre, le choix des paramètres d'autocorrélations, utilisés pour définir les champs aléatoires, est discuté.L'applicabilité des deux méthodes est évaluée à l'aide de différentes séries expérimentales présentant des effets d'échelle particulièrement statistique. En outre, la méthode EFS est utilisée pour compléter le modèle EF simplifié de la maquette d'enceinte à double paroi VeRCoRs (échelle 1/3). Les incertitudes sur la résistance à la traction, à cette échelle, sont modélisées à l'aide d'un champ aléatoire autocorrelé indépendant à chaque levée. La propagation des incertitudes, à l'état initial, montre sa pertinence dans l'estimation des positions de fissures. / This thesis is a contribution to the modeling of the spatial variability of tensile strength of concrete structures, at different scales, and its influence on concrete cracking pattern. Particularly, a size effect law and random fields are used through two approaches:On the one hand, an analytical probabilistic approach of the Weakest Link and Localization (WL2) method is proposed. This method estimates the distribution of the tensile strength, at different scales, accounting for the stress redistributions around the weakest point.It depends on a scale length, whose identification is discussed. This scale length accounts for spatial randomness of the concrete tensile strengthOn the other hand, another contribution of this thesis is the development of a Stochastic Finite Element (SFE) method, used to model both size effect and the spatial variability of the tensile strength. The method consists first on defining a random field, using the mean tensile strength estimated from the analytical approach of WL2. Then, discretized autocorrelated random field realizations are generated. Moreover, the choice of autocorrelation parameters, used to define the random fields, is discussed.The applicability of both methods is evaluated using various experimental series exhibiting particularly statistical size effect. Furthermore, the SFE method is used to complete the simplified FE model of a 1/3 mock-up of a double-wall containment building. The uncertainties on the tensile strength, at this scale, are modeled using independent autocorrelated random field at each scale. Uncertainties propagation, at initial state, shows its pertinence in the estimation of crack positions.