Previous research efforts have shown that fish and macroinvertebrates are responsive to fine sediment in streambeds. Excess fine sediment (<2mm in diameter) impairs over 40,000 miles of streams in the U.S., degrading habitat quality for many aquatic species. Embeddedness (emb, %), a measure of fine sediment in gravel bed streams, is negatively correlated with bankfull shear velocity (u*, m/s). This relationship can be modeled by emb = au*b, with baseline coefficient values of a = 10 and b = –1. The purpose of this thesis was to investigate the applicability of this relationship across the U.S., to begin to quantify the variation of embeddedness in time, and to determine the applicability of embeddedness as a habitat metric for lotic biota. The areas that were studied included Stroubles Creek at the Virginia Tech Stream Lab, the Upper Roanoke River Basin in southwest Virginia, and Level II and III ecoregions nationwide with the U.S. EPA National Rivers and Streams Assessment dataset. Nationally, measurements of embeddedness were higher than modeled in areas with higher sediment supply, and lower than modeled in regions with low fine sediment supply. By calculating shear velocity through remotely sensed channel geometry metrics, embeddedness may be predicted throughout a stream network. Various biotic metrics were found to be correlated to embeddedness, with regional variation. Burrowing macroinvertebrate taxa, which may use increased sand to escape predation, increased with increasing embeddedness while the number of Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa, the number of lithophilic spawning fish, and the number of salmonid taxa decreased with increasing embeddedness. Highly embedded substrate is generally considered poor habitat, which was supported by a trend of decreasing intolerant fish taxa with increasing embeddedness. Richness (total number of taxa) did not show a significant correlation, indicating that embeddedness, and fine sediment in general, is not necessarily an impairment to all stream habitat, but is impactful for particular taxa. / Master of Science / Previous research has shown that fish and macroinvertebrates are responsive to fine sediment in streambeds. Excess fine sediment (sand, silt, and clay) impairs over 40,000 miles of streams in the U.S., degrading habitat quality for many aquatic species. Embeddedness (emb, %), a measure of fine sediment in gravel bed streams, decreases with increasing bankfull shear velocity (u*, m/s), a measure of a stream's ability to move a particular size of sediment. The purpose of this thesis was to investigate the relationship between embeddedness and shear velocity in varying areas, to begin to quantify the variation of embeddedness in time, and to determine the applicability of embeddedness as a habitat metric for stream biota. The areas that were studied included Stroubles Creek at the Virginia Tech Stream Lab, the Upper Roanoke River Basin in southwest Virginia, and Level II and III ecoregions nationwide with the U.S. EPA National Rivers and Streams Assessment dataset. Nationally, measurements of embeddedness were higher in areas that may have higher sediment supply, and lower in regions with low fine sediment supply. By calculating shear velocity with remotely available stream data, embeddedness may be predicted throughout a stream network and compared with biota in those locations. Various biotic metrics were found to be correlated to embeddedness, with regional variation. Burrowing macroinvertebrate taxa, which may use increased sand to escape predation, increased with increasing embeddedness while the number of Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa, the number of lithophilic spawning fish, and the number of salmonid taxa decreased. Highly embedded substrate is generally considered poor habitat, which was supported by a trend of decreasing intolerant fish taxa with increasing embeddedness.

The standard model of the thermal and chemical structure of cratons has been scrutinized in recent years as additional data have been collected. Recent seismological and petrological studies indicate that the notion of cratonic lithosphere as a thick thermal boundary layer with a very depleted and dehydrated composition may be too simplistic and does not fully explain all aspects of the seismological and petrological observations. We hypothesized that the cratonic lithosphere may be more complicated and designed an experiment to investigate its thermal, chemical, and mineralogical properties using a global database of fundamental mode Rayleigh surface waves. To test this hypothesis, the phase velocities of Rayleigh wave that travel paths primarily over cratons were selected. A 1-D global craton phase velocity profile was generated from these observations and compared to predicted phase-velocity curves using two different forward modeling techniques. With the first approach, profiles of shear velocity were generated based on educated guesses of upper mantle temperatures using geotherms. With the second approach, profiles of shear velocity were generated using random permutations about 1-D global model STW105. In total 5,625 geotherm and 80,000 random 1-D forward models were generated for comparison. Each shear velocity model was converted to phase velocity and compared to the observed range of cratonic phase velocities, defined as within one standard deviation of the mean. This method was able to constrain shear velocity in cratons relatively well though the 1-D profiles deviate at depths shallower than 100 km. Shear velocity is faster than PREM/STW105 to depths greater than 200 km with constantly increasing velocity with depth in the random model and a low velocity layer at 100-150 km.

abstract: This research investigates Earth structure in the core-mantle boundary (CMB) region, where the solid rocky mantle meets the molten iron alloy core. At long wavelengths, the lower mantle is characterized by two nearly antipodal large low shear velocity provinces (LLSVPs), one beneath the Pacific Ocean the other beneath Africa and the southern Atlantic Ocean. However, fine-scale LLSVP structure as well as its relationship with plate tectonics, mantle convection, hotspot volcanism, and Earth's outer core remains poorly understood. The recent dramatic increase in seismic data coverage due to the EarthScope experiment presents an unprecedented opportunity to utilize large concentrated datasets of seismic data to improve resolution of lowermost mantle structures. I developed an algorithm that identifies anomalously broadened seismic waveforms to locate sharp contrasts in shear velocity properties across the margins of the LLSVP beneath the Pacific. The result suggests that a nearly vertical mantle plume underlies Hawaii that originates from a peak of a chemically distinct reservoir at the base of the mantle, some 600-900 km above the CMB. Additionally, acute horizontal Vs variations across and within the northern margin of the LLSVP beneath the central Pacific Ocean are inferred from forward modeling of differential travel times between S (and Sdiff) and SKS, and also between ScS and S. I developed a new approach to expand the geographic detection of ultra-low velocity zones (ULVZs) with a new ScS stacking approach that simultaneously utilizes the pre- and post-cursor wavefield.. Strong lateral variations in ULVZ thicknesses and properties are found across the LLSVP margins, where ULVZs are thicker and stronger within the LLSVP than outside of it, consistent with convection model predictions. Differential travel times, amplitude ratios, and waveshapes of core waves SKKS and SKS are used to investigate CMB topography and outermost core velocity structure. 1D and 2D wavefield simulations suggest that the complicated geographic distribution of observed SKKS waveform anomalies might be a result of CMB topography and a higher velocity outermost core. These combined analyses depict a lowermost mantle that is rich in fine-scale structural complexity, which advances our understanding of its integral role in mantle circulation, mixing, and evolution. / Dissertation/Thesis / Ph.D. Geological Sciences 2012

[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.

This master thesis is divided into two parts: theoretical and practical one. In the theoretical part there is described hydraulic roughness, velocity distribution in the case of hydraulically rough surface and the process of grain sorting in surface layer. The practical part of the thesis resolves the influence of surface layer on hydraulic roughness of bed, expressed by Nikuradse sand grain size ks. The results are formulas explaining dependence of ks on characteristic grain size dx from grain-size distribution curve and comparison with coefficient ks according to different authors.