Incomplete data represents a major challenge for a successful prediction and subsequent removal of multiples. In this paper, a new method will be represented that tackles this challenge in a two-step approach. During the first step, the recenly developed curvelet-based recovery by sparsity-promoting inversion (CRSI) is applied to the data, followed by a prediction of the primaries. During the second high-resolution step, the estimated primaries are used to improve the frequency content of the recovered data by combining the focal transform, defined in terms of the estimated primaries, with the curvelet transform. This focused curvelet transform leads to an improved recovery, which can subsequently be used as input for a second stage of multiple prediction and primary-multiple separation.

n this paper, two different applications of phase transitions to exploration seismology will be discussed. The first application concerns a phase diagram ruling the recovery conditions for seismic data volumes from incomplete and noisy data while the second phase transition describes the behavior of bi-compositional mixtures as a function of the volume fraction. In both cases, the phase transitions are the result of randomness in large system of equations in combination with nonlinearity. The seismic recovery problem from incomplete data involves the inversion of a rectangular matrix. Recent results from the field of "compressive sensing" provide the conditions for a successful recovery of functions that are sparse in some basis (wavelet) or frame (curvelet) representation, by means of a sparsity ($\ell_1$-norm) promoting nonlinear program. The conditions for a successful recovery depend on a certain randomness of the matrix and on two parameters that express the matrix' aspect ratio and the ratio of the number of nonzero entries in the coefficient vector for the sparse signal representation over the number of measurements. It appears that the ensemble average for the success rate for the recovery of the sparse transformed data vector by a nonlinear sparsity promoting program, can be described by a phase transition, demarcating the regions for the two ratios for which recovery of the sparse entries is likely to be successful or likely to fail. Consistent with other phase transition phenomena, the larger the system the sharper the transition. The randomness in this example is related to the construction of the matrix, which for the recovery of spike trains corresponds to the randomly restricted Fourier matrix. It is shown, that these ideas can be extended to the curvelet recovery by sparsity-promoting inversion (CRSI) . The second application of phase transitions in exploration seismology concerns the upscaling problem. To counter the intrinsic smoothing of singularities by conventional equivalent medium upscaling theory, a percolation-based nonlinear switch model is proposed. In this model, the transport properties of bi-compositional mixture models for rocks undergo a sudden change in the macroscopic transport properties as soon as the volume fraction of the stronger material reaches a critical point. At this critical point, the stronger material forms a connected cluster, which leads to the creation of a cusp-like singularity in the elastic moduli, which in turn give rise to specular reflections. In this model, the reflectivity is no longer explicitly due to singularities in the rocks composition. Instead, singularities are created whenever the volume fraction exceeds the critical point. We will show that this concept can be used for a singularity-preserved lithological upscaling.

Methane hydrate formation and dissociation studies from high water content (>60 vol% water) – crude oil emulsions were performed. The hydrate and emulsion system was characterized using two particle size analyzers and conductivity measurements. It was observed that hydrate formation and dissociation from water-in-oil (W/O) emulsions destabilized the emulsion, with the final emulsion formulation favoring a water continuous state following re-emulsification. Hence, following dissociation, the W/O emulsion formed a multiple o/W/O emulsion (60 vol% water) or inverted at even higher water cuts, forming an oil-in-water (O/W) emulsion (68 vol% water). In contrast, hydrate formation and dissociation from O/W emulsions (≥71 vol% water) stabilized the O/W emulsion.

Two internationally-partnered research well programs, in 1998 and 2002, studied the Mallik gas hydrate accumulation in the Mackenzie Delta, Canada. Gas hydrate bearing intervals were cored, logged and production tested thus establishing Mallik as an excellent site for testing geophysical imaging techniques. Here, we apply a model-based acoustic impedance inversion technique to 3D seismic reflection data acquired over the Mallik area to characterize gas hydrate occurrences and to help define their spatial extent away from well control. Sonic logs in Mallik research wells show that P-wave velocity of sediments increases with hydrate saturation, enough to produce detectable reflections for the lower two of three known gas hydrate zones. The inversion method converts these reflections into acoustic impedances from which velocity and hydrate saturation can be estimated. Acoustic impedance inversion results indicate that the deepest gas hydrate zone covers an area of approximately 900,000 m2. With some assumptions on the lateral continuity of gas hydrate saturation, porosity and thickness measured at the wells, we estimate that this zone contains approximately 771x106 m3 of gas at standard atmospheric pressure. At a regional scale, results allowed the detection of a high-velocity area near the A-06 well, about 6 km south-east of 5L-38. We infer that the high velocity area corresponds to a gas hydrate accumulation. Logging data in A-06 indicate the presence of gas hydrates in this area and support our interpretation.

This thesis is focused on automatic detection of white matter lesions (WML) in Fluid Attenuation Inversion Recovery (FLAIR) Magnetic Resonance Images (MRI) of the brain. There is growing interest within the medical community regarding WML, since the total WML volume per patient (lesion load) was shown to be related to future stroke as well as carotid disease. Manual segmentation of WML is time consuming, labourious, observer-dependent and error prone. Automatic WML segmentation algorithms can be used instead since they give way to lesion load computation in a quantitative, efficient, reproducible and reliable manner. FLAIR MRI are affected by at least two types of degradations, including additive noise and the partial volume averaging (PVA) artifact, which affect the accuracy of automated algorithms. Model-based methods that rely on Gaussian distributions have been extensively used to handle these two distortions, but are not applicable to FLAIR with WML. The distribution of noise in multicoil FLAIR MRI is non-Gaussian and the presence of WML modifies tissue distributions in a manner that is difficult to model. To this end, the current thesis presents a novel way to model PVA artifacts in the presence of noise. The method is a generalized and adaptive approach, that was applied to a variety of MRI weightings (with and without pathology) for robust PVA quantification and tissue segmentation. No a priori assumptions are needed regarding class distributions and no training samples or initialization parameters are required. Segmentation experiments were completed using simulated and real FLAIR MRI. Simulated images were generated with noise and PVA distortions using realistic brain and pathology models. Real images were obtained from Sunnybrook Health Sciences Centre and WML ground truth was generated through a manual segmentation experiment. The average DSC was found to be 0.99 and 0.83 for simulated and real images, respectively. A lesion load study was performed that examined interhemispheric WML volume for each patient. To show the generalized nature of the approach, the proposed technique was also employed on pathology-free T1 and T2 MRI. Validation studies show the proposed framework is classifying PVA robustly and tissue classes are segmented with good results.

This thesis is focused on automatic detection of white matter lesions (WML) in Fluid Attenuation Inversion Recovery (FLAIR) Magnetic Resonance Images (MRI) of the brain. There is growing interest within the medical community regarding WML, since the total WML volume per patient (lesion load) was shown to be related to future stroke as well as carotid disease. Manual segmentation of WML is time consuming, labourious, observer-dependent and error prone. Automatic WML segmentation algorithms can be used instead since they give way to lesion load computation in a quantitative, efficient, reproducible and reliable manner. FLAIR MRI are affected by at least two types of degradations, including additive noise and the partial volume averaging (PVA) artifact, which affect the accuracy of automated algorithms. Model-based methods that rely on Gaussian distributions have been extensively used to handle these two distortions, but are not applicable to FLAIR with WML. The distribution of noise in multicoil FLAIR MRI is non-Gaussian and the presence of WML modifies tissue distributions in a manner that is difficult to model. To this end, the current thesis presents a novel way to model PVA artifacts in the presence of noise. The method is a generalized and adaptive approach, that was applied to a variety of MRI weightings (with and without pathology) for robust PVA quantification and tissue segmentation. No a priori assumptions are needed regarding class distributions and no training samples or initialization parameters are required. Segmentation experiments were completed using simulated and real FLAIR MRI. Simulated images were generated with noise and PVA distortions using realistic brain and pathology models. Real images were obtained from Sunnybrook Health Sciences Centre and WML ground truth was generated through a manual segmentation experiment. The average DSC was found to be 0.99 and 0.83 for simulated and real images, respectively. A lesion load study was performed that examined interhemispheric WML volume for each patient. To show the generalized nature of the approach, the proposed technique was also employed on pathology-free T1 and T2 MRI. Validation studies show the proposed framework is classifying PVA robustly and tissue classes are segmented with good results.

Des mesures de résistivité électrique et des campagnes d'observations géologiques ont été menées pour cartographier le contact sédiment/roche basale ainsi que les structures d'impact associées au cratère d'impact Bosumtwi datant de 1,07 millions d'années. Le cratère de 10,5 km de diamètre s'est formé dans des roches métamorphiques du Précambrien (2,1 à 2,2 milliard d'années), d'origine sédimentaire et volcanique. Il est actuellement rempli par le lac Bosumtwi de 8,5 km de diamètre. Ce cratère est la source des tektites et microtektites dispersées jusqu'en Côte d'Ivoire et au large des côtes ouest africaine. La campagne de mesures éophysiques consiste en 16 tomographies de résistivité électrique effectuées radialement des rives du lac vers les bords du cratère d'impact. Chaque profil utilise un système d'acquisition multi - électrodes avec une distance minimum entre les électrodes de 5 m. Les données ont été corrigées des effets topographiques et inversées en utilisant le programme commercial d'inversion Res2DInv, avec la norme L1 considérée plus robuste. La zone comprise entre les rives du lac et le bord externe du cratère de divise en trois formations géologiques principales. Les régions de faibles résistivités (< 64 .m) représentent les sédiments de lac. Les zones de resistivités moyennes (entre 128 et 200 .m) sont interprétées comme des brèches liées à l'impact, en dikes, allochtones ou parautochtones. Les régions de hautes résistivités (> 128 .m) représentent les roches métamorphiques sous-jacentes, d'origine volcanique ou sédimentaire. Les profils de résistivités permettent de retrouver la géométrie et l'extension latérale de ces trois types de roches. Une correspondance directe entre la lithologie observée en surface et les structures mises en évidence par les mesures de résistivité électrique dans le sous-sol est observée à Dwamam au Sud-Est dulac. À Dwamam, les sédiments sont environ à 200 m de la rive du lac et s'étendent environ sur 400 m vers les les bords du cratère, à la différence des autres zones où ont pu être cartographiés les sédiments. La topographie du contact sédiment/roche basale présente une direction particulière NE-SO avec un pendage variant entre 16 degrés au NE et 36 degrés au SO. Une majorité de fractures ont été remarquées dans le SO, remplies par des clasts et des brèches d'impacts. Les failles sont surtout présentent à l'Ouest du lac. En moyenne elles présentent un pendage variant entre 60o à l'Est et 80 degrés à l'Ouest du cratère. Des analyses statistiques ont été effectuées sur les directions et les pendages des failles selon les loi de von Mises et Fisher. Elles démontrent que les failles s'alignent préférentiellement le long de deux directions principales. L'analyse cumulée de la surface de contact sédiment/roche, des failles et de la localisation du champ de dispersion des tektites indique que le bolide d'environ 0,8 à 1 km de diamètre responsable du cratère est arrivé du NE. Les résultats démontrent que les panneaux de résistivité électrique fournissent des informations utiles pour l'étude des cratères d'impact.

Cloud computing systems, like MapReduce and Pregel, provide a scalable and fault tolerant environment for running computations at massive scale. However, these systems are designed primarily for data intensive computational tasks, while a large class of problems in scientific computing and business analytics are computationally intensive (i.e., they require a lot of CPU in addition to I/O). In this thesis, we investigate the use of cloud computing systems, in particular MapReduce, for computationally intensive problems, focusing on two classic problems that arise in scienti c computing and also in analytics: maximum clique and matrix inversion. The key contribution that enables us to e ectively use MapReduce to solve the maximum clique problem on dense graphs is a recursive partitioning method that partitions the graph into several subgraphs of similar size and running time complexity. After partitioning, the maximum cliques of the di erent partitions can be computed independently, and the computation is sped up using a branch and bound method. Our experiments show that our approach leads to good scalability, which is unachievable by other partitioning methods since they result in partitions of di erent sizes and hence lead to load imbalance. Our method is more scalable than an MPI algorithm, and is simpler and more fault tolerant. For the matrix inversion problem, we show that a recursive block LU decomposition allows us to e ectively compute in parallel both the lower triangular (L) and upper triangular (U) matrices using MapReduce. After computing the L and U matrices, their inverses are computed using MapReduce. The inverse of the original matrix, which is the product of the inverses of the L and U matrices, is also obtained using MapReduce. Our technique is the rst matrix inversion technique that uses MapReduce. We show experimentally that our technique has good scalability, and it is simpler and more fault tolerant than MPI implementations such as ScaLAPACK.

A sedimentological and geomorphologic investigation southeast of the City of Guelph, Ontario was undertaken to determine the nature, trends in distribution, and origin of subsurface sediments in the Paris moraine. Sediments were investigated by drilling five cored-holes, mapping geomorphic elements, and creating a database of existing data. Nine broadly encompassing and reoccurring lithofacies were identified, ranging from gravel to clayey silt. The general transverse trend of geomorphic elements across the moraine consists of a frontslope, hummocky, and backslope element. Sediment-landform associations were identified from the synthesis of cored-hole, geomorphic element mapping, and lithologic cross-section data. Based on these results, the Paris Moraine is thought to be the remnants of an ice-cored controlled moraine. The relief inversion process responsible for the formation of the controlled moraine creates a horizontally and vertically variable distribution of lithofacies. Hydrogeologic properties of the moraine sediments will likely be similarly spatially variable and difficult to predict. / Ontario Research Fund, NSERC, OMAFRA

Annually and subannually laminated lacustrine sediments potentially contain a wide range of information that can be interpreted for paleoenvironmental reconstructions. These laminae are produced by the physical and biological processes that operate in the lake and in the surrounding terrestrial environment. However, identification of the influences that control laminae production may not be straightforward, and other processes may subtly influence the overall depositional sequence. This thesis examines two different depositional environments on Colin Archer Peninsula, Devon Island, Canada, with the objective of identifying the factors that influence subannual sediment deposition and how the resultant sedimentary structures can be used as indicators of paleoenvironmental conditions. In proglacial Lake R, clastic sediment deposition is controlled primarily by subannual meteorological conditions. Periods of positive air temperature or large rainfall events produce discernable laminae that, when combined, form a varve sequence. However, overarching geomorphic controls influence the delivery of sediment to the lake and may reduce or enhance the hydrometeorological signal contained in the varves. An additional influence for calibration of the varve record to meteorological observations is the role that melt season thermal inversions have on temperature extrapolation in the High Arctic. Meteorological stations at sea level may not be representative of the surrounding region, thereby reducing the accuracy of vertical temperature estimation. Investigation of the inversions in the central Canadian High Arctic demonstrated that melt season inversions are common and increased inversion frequency may potentially have influenced enhanced glacial melt since the late 1980s, with implications for proglacial lake sediment transport and deposition. In coastal Lake J, late Holocene sediments record a relatively unusual accumulation of microbially induced sedimentary structures (MISS). Such a record has not been previously described in the circum-Arctic, although they are known to exist elsewhere. These sediments are produced by the interaction between clastic sedimentation and cyanobacterial growth and production. Although chronological constraint could not be assigned with certainty to the record, statistical study of the laminated sequence suggested a dominant pattern that is plausibly annual. A heuristic model of annual sediment accumulation was developed in order to explore the potential for quasi-annual paleoenvironmental interpretations. / Thesis (Ph.D, Geography) -- Queen's University, 2008-05-22 09:55:12.184