This thesis describes a study of the application of linear programming, a mathematical optimization technique, to the problem of operating a system of flood control reservoirs in the most efficient way for maximum flood peak reduction. The reservoir system studied was one which is proposed for flood control in the Fraser River Basin and for which preliminary designs have been made. The proposed sites are in the headwater areas of the river basin, remote from the area to be protected. A channel routing method which was linear was required for use with the linear programming technique. A method was developed which was based on monoclinal wave theory. Several different cases were studied in which the reservoir capacities and combinations of reservoirs included in the system were varied. The results show the maximum regulation which is available from each combination of reservoirs and identify the minimum storage capacities required at each site. Application of the technique in planning studies and in real-time reservoir operation is discussed. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Orientador: Alberto Luiz Francato / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-26T14:59:45Z (GMT). No. of bitstreams: 1 Costa_CarlosAntonioSeverino_M.pdf: 4423494 bytes, checksum: efb5bbedc885642da6b53bdbca912fc4 (MD5) Previous issue date: 2014 / Resumo: O controle de cheias no Brasil e no mundo tem sido alvo de estudo nos centros de pesquisa e um desafio para os governantes. As inundações em muitos países têm sido consideradas como um dos maiores desastres naturais. Anualmente, centenas de bilhões de dólares de prejuízos crescentes vêm se verificando em todo o mundo, devido aos riscos cada vez maiores às benfeitorias, culturas agrícolas, obras de infraestrutura, populações ribeirinhas, áreas urbanas etc. Centros de pesquisas de todo o mundo têm abordado o assunto e proposto medidas de controle a inundação, tanto estruturais como não estruturais. Novas metodologias para operação de reservatórios, buscando sua melhor capacidade de controle das cheias e ao mesmo tempo atendendo aos outros usos da água, têm sido apresentadas de modo a minimizar os impactos das cheias e, por conseguinte, reduzir riscos e prejuízos junto às comunidades. A motivação desta dissertação foi desenvolver uma metodologia que possa avaliar o custo hidroenergético da manutenção de volumes de espera para o controle de cheias nos reservatórios, mais especificamente em estabelecer uma política de armazenamento das cheias de forma a minimizar os impactos para a geração de energia hidrelétrica. Tal tarefa foi realizada utilizando o modelo CooperMax (FRANCATO, 2014), com adaptações para a análise de cheias / Abstract: Flood control in Brazil and abroad has been studied in research centers and has posed a challenge to governments. Floods in many countries have been regarded as one of the greatest natural disasters. Every year hundreds of billions of dollars of rising losses have been observed around the world due increasing risks to property, crops, infrastructure, river populations, urban areas etc. Research centers around the world have approached the subject and proposed flood control measures, both structural and non-structural. New methodologies for reservoir operation for better flood controls, taking into account other uses of water, have been proposed in order to minimize the impact of flood and therefore reduce risks and losses in the communities. The motivation of this thesis was to develop a methodology to evaluate the hydropower cost of maintaining a storage volume for flood control in the reservoirs, more specifically in establishing a policy of flood storage in order to minimize impacts in hydropower generation. This task was performed using the CooperMax model, adapted for the analysis of floods / Mestrado / Recursos Hidricos, Energeticos e Ambientais / Mestre em Engenharia Civil

Few genomic and metagenomic studies have focused on freshwater systems in the last years. Most of the studies carried out on these particular environments so far rely on microscopy, physiology, phenotypic observations, individual genes and 16S rRNA sequencing. Here, we shed light on microbial communities from oligotrophic and mesotrophic freshwater systems using high-throughput deep sequencing metagenomics and genome-resolved metagenomics. We have focused on the study of ubiquitous and cosmopolitan microbial groups from two temperate Spanish reservoirs (Tous, Amadorio). Among these, we studied freshwater picocyanobacteria from Synechococcus and Cyanobium genera, which so far have not been well characterized at the genomic level, compared to the marine representatives. In particular, we were able to isolate two of the most abundant picocyanobacteria from Tous reservoir, which were previously studied via metagenomics. These picocyanobacteria are not only abundant in this reservoir but are widely distributed in different freshwater and brackish systems. In this work we also shed light on some of the first freshwater representatives of the phylum Verrucomicrobia, that are ecologically uncharacterized in freshwater systems about which relatively little is known. We discovered a wide range of metabolisms in these microbes, ranging from nitrogen fixation and photoheterotrophy via rhodopsin pumps to important contributions in the degradation of recalcitrant matter and polysaccharides. We also include the first metagenomic study of the microbial communities under the ice waters of the largest (by volume) ultraoligotrophic lake in the world, Lake Baikal. This study has provided a first glimpse and a particular microbial composition on the sub-ice, having found an unusual fraction of Verrucomicrobia and new microbial lineages from many typical freshwater phyla, including the first freshwater representative of the groups I/II of SAR11 lineage and novel genomes of Proteobacteria, Thaumarchaeaota, Gemmatimonadetes, Cyanobacteria, Planctomycetes, Bacteroidetes, Acidobacteria, Nitrospirae, Verrucomicrobia or Actinobacteria.

Lake Manassas is an approximate 706 acre man-made lake located in greater Prince William County near the town of Gainesville, Virginia. The lake was created in 1968 on Broad Run to serve as the primary water supply for the City of Manassas and its residents. The Lake Manassas watershed lies within the greater Occoquan River watershed which drains into the Potomac River and Chesapeake Bay. Water within Lake Manassas and its tributaries has been monitored since 1971 and this thesis presents a comprehensive limnological analysis of the Lake with an analysis of water quality impacts over time. Lake Manassas remains an enriched or eutrophic system, meaning the levels of nutrients and biomass production in lake waters is above desired standards. Nutrient loading occurs via a stream network with the largest contributor being Broad Run which is consistent with previous water quality studies. The lake serves as the sole water source for nearly 40,000 residents and businesses and ensuring clean and safe water is of significant importance. Close monitoring in conjunction with the implementation of appropriate management practices within the watershed are necessary to prevent water quality from becoming significantly degraded. / Master of Science

No description available.

Geologic sequestration of CO2 into unmineable coal seams is proposed as a way to mitigate the greenhouse gas effect and potentially contribute to economic prosperity through enhanced methane recovery. In 2009, the Virginia Center for Coal and Energy Research (VCCER) injected 907 tonnes of CO2 into one vertical coalbed methane well for one month in Russell County, Virginia (VA). The main objective of the test was to assess storage potential of coal seams and to investigate the potential of enhanced gas recovery. In 2014, a larger scale test is planned where 20,000 tonnes of CO2 will be injected into three vertical coalbed methane wells over a period of a year in Buchanan County, VA. During primary coalbed methane production and enhanced production through CO2 injection, a series of complex physical and mechanical phenomena occur. The ability to represent the behavior of a coalbed reservoir as accurately as possible via computer simulations yields insight into the processes taking place and is an indispensable tool for the decision process of future operations. More specifically, the economic viability of projects can be assessed by predicting production: well performance can be maximized, drilling patterns can be optimized and, most importantly, associated risks with operations can be accounted for and possibly avoided. However, developing representative computer models and successfully simulating reservoir production and injection regimes is challenging. A large number of input parameters are required, many of which are uncertain even if they are determined experimentally or via in-situ measurements. Such parameters include, but are not limited to, seam geometry, formation properties, production constraints, etc. Modeling of production and injection in multi-seam formations for hydraulically fractured wells is a recent development in coalbed methane/enhanced coalbed methane (CBM/ECBM) reservoir modeling, where models become even more complex and demanding. In such cases model simulation times become important. The development of accurate simulation models that correctly account for the behavior of coalbeds in primary and enhanced production is a process that requires attention to detail, data validation, and model verification. A number of simplifying assumptions are necessary to run these models, where the user should be able to balance accuracy with computational time. In this thesis, pre- and post-injection simulations for the site in Russell County, VA, and preliminary reservoir simulations for the Buchanan County, VA, site are performed. The concepts of multi-well, multi-seam, explicitly modeled hydraulic fractures and skin factors are incorporated with field results to provide accurate modeling predictions. / Ph. D.

Petrophysical properties are fundamental to understanding fluid flow processes in hydrocarbon reservoirs. Special Core Analysis (SCAL) routinely used in industry are time-consuming, expensive, and often destructive. Alternatively, easily available thin section data is lacking the representation of pore space in 3D, which is a requisite for generating pore network models (PNM) and computing petrophysical properties. In this study, these challenges were addressed using a numerical SCAL workflow that employs pore volume reconstruction from thin section images obtained from confocal laser scanning microscopy (CLSM). A key objective is to investigate methods capable of 2D to 3D reconstruction, to obtain PNM used for the estimation of transport properties. Representative thin sections from a well-known Middle-Eastern carbonate formation were used to obtain CLSM images. The thin-sections were specially prepared by spiking the resin with UV dye, enabling high-resolution imaging. The grayscale images obtained from CLSM were preprocessed and segmented into binary images. Generative Adversarial Networks (GAN) and Two-Point Statistics (TPS) were applied, and PNM were extracted from these binary datasets. Porosity, Permeability, and Mercury Injection Porosimetry (MIP) on the corresponding core plugs were conducted and an assessment of the properties computed from the PNM obtained from the reconstructed 3D pore volume is presented. Moreover, the results from the artificial pore networks were corroborated using 3D confocal images of etched pore casts (PCE). The results showed that based on visual inspection only, GAN outperformed TPS in mimicking the 3D distribution of pore scale heterogeneity, additionally, GAN and PCE outperformed the results of MIP obtained by TPS on the Skeletal-Oolitic facies, without providing a major improvement on more heterogeneous samples. All methods captured successfully the porosity while absolute permeability was not captured. Formation resistivity factor and thermal conductivity showcased their strong correlation with porosity. The study thus provides valuable insights into the application of 2D to 3D reconstruction to obtain pore network models of heterogeneous carbonate rocks for petrophysical characterization for quick decision. The study addresses the following important questions: 1) how legacy thin sections can be leveraged to petrophysically characterize reservoir rocks 2) how reliable are 2D to 3D reconstruction methods when predicting petrophysical properties of carbonates.

No description available.

The American cockroach, Periplaneta americana (L.), is an important urban pest due to its ability to invade residential and commercial structures from non-residential reservoirs. Extensive field studies were conducted in a large urban apartment complex, Lincoln Terrace (LT), managed by the Roanoke Redevelopment and Housing Authority (RRHA), in Roanoke, Virginia. Inspection in the RRHA-LT complex corroborated well with other researchers' finding that sewer and storm drainage systems are the principal reservoirs for P. americana population in the temperate urban environn1ent. Investigations provided new evidence that basements of the RRHA-LT apartment buildings served as secondary reservoirs for this pest species. Environmental and ecological parameters that characterize basements as important P. americana population reservoir foci were studied. Understanding how populations function in the urban environment is as important as identifying P. americana population reservoirs. Over two-years of fleld investigations demonstrated that foraging activity of P. americana was seasonal. A study of a simulated population of caged American cockroaches maintained in a basement environment confirmed that their foraging activity was seasonal. Foraging seasonality characterizes the seasonal pest status of this cockroach species in the temperate urban environment. Therefore, seasonally oriented control or management strategies for this pest species are proposed and discussed. Lipids, carbohydrates, and proteins of American cockroach adults were analyzed and quantified on a monthly basis for a year. Seasonal foraging activity was reflected by seasonal changes of metabolic reserves in this species. Low foraging activity in the colder, winter months characterized an overwintering period of P. americana populations in the urban environment. Lipids were the principal metabolic reserve for overwintering cockroaches, and accounted for a 22% of dry body weight loss in females and 18% in males. Proteins accounted for approximately 10% of the dry body weight loss for overwintering females and males. Glycogen concentration per unit dry weight increased 11 % to 15% during the overwintering period. This change suggests that glycogen may function as a cold hardiness substance rather than as a energy reserve during overwintering. Nutrient deficits of post-overwintering individuals in the population explained the underlying physiological driving force for significantly ir~creased foraging activities in the spring. Caged P. americana demonstrated a high reproductive potentia] in the basement environment. High reproductive rate created protein and lipid deficits in adults that required increased foraging for food and increased cannibalism of oothl!cae and young nymphs. Approximately 33% of the oothecae and 28% of nymphs were cannibalized in the caged population. / Ph. D.

CO2 injection has demonstrated significant potential for enhanced oil recovery techniques in unconventional reservoirs, but there exists many challenges in optimizing its operations due to the limited understanding of CO2-oil transport mechanisms in these systems. This dissertation addresses these challenges using molecular dynamics (MD) simulations by investigating the gas and oil transport behaviors and properties within single nanopores under reservoir conditions. The first study examines the exchange dynamics of decane with CO2 and CH4 in a 4 nm-wide calcite nanopore. It is shown that both gases form distinct adsorbed and free molecular populations upon entering the pores, leading to different extraction dynamics. Notably, CO2-decane exchange is initially driven by adsorbed populations, with a transition to free populations later; whereas CH4 -decane exchange follows the opposite pattern. Despite these differences, the transport of both gases apparently follows the same diffusive behavior, with CH4 exhibiting higher effective diffusivities. By calculating self-diffusivities at various relevant compositions, it is found they do not always align well with their effective diffusivities. The second study therefore focuses on Maxwell-Stefan (M-S) diffusivities as a more comprehensive framework to describe the diffusion of CO2-decane mixtures in the first study. It is found that D12 (CO2-decane interactions) remains relatively constant across compositions, unlike bulk mixtures, while D1,s (CO2-wall interactions) increases sharply with CO2 loading. In contrast, D2,s (decane-wall interactions) shows a nonmonotonic trend and, unexpectedly, becomes negative under certain compositions. These phenomena are linked to the strong adsorption of CO2, causing significant density heterogeneity and reduced mobility. Using a multi-task Gaussian process regression model, the M−S diffusivities can be predicted with a relative root mean square error below 10%, significantly reducing computational demand for their practical usage. The third study examines concentration gradient driven diffusio-osmosis of oil-CO2 mixtures within silica and calcite nanopores. Despite higher CO2 enrichment near calcite walls, diffusio-osmotic is only marginally stronger than in silica pores, which is attributed to the variations in interfacial fluid structures and hydrodynamic properties in different pores. Continuum simulations suggest that diffusio-osmosis becomes increasingly significant compared to Poiseuille flow as pore width decreases. The fourth study investigates the oil mixture (C10+C19) recovery from a 4 nm-wide calcite dead-end pore with and without CO2 injection. It was found that CO2 accelerates oil recovery and reduces selectivity for lighter components (e.g., C10) compared to the recovery without CO2. Such improvements are influenced by interfacial and bulk phenomena, including adsorption competition and solubilization effects. Together, these studies provide quantitative insights into CO2-oil transport mechanisms and properties in nanopores. Such insights can help develop better reservoir simulators to guide the optimization of CO2 injection-based enhanced oil recovery in unconventional reservoirs. / Doctor of Philosophy / Recovering oil from unconventional reservoirs—types of underground rock formations that trap oil in extremely tiny pores, much smaller than the thickness of a strand of hair—is one of the biggest challenges in the petroleum industry. The narrow pore size greatly increases the fraction of the oil flow, and many pores are not even connected, which stops oil to flow out on its own, making it much harder to extract from these reservoirs. Injecting gases into the reservoirs, like carbon dioxide (CO2), has become a promising solution. This method not only helps to push the oil out but also allows part of the injected CO2 to be stored underground, reducing its impact on the atmosphere. To make this process work better, we need in depth understandings of how oil and gas move in these tiny rock spaces. Four studies have been conducted to elucidate the transport phenomena in CO2 injection-based enhanced oil recovery. The first study finds that the exchange between trapped oil and CO2 is significantly influenced by how oil and CO2 stick to the walls of these tiny pores. However, it is observed that commonly used characterization methods do not always work well in the prediction of recovery behavior, indicating the need for a better framework to describe this process. To address this problem, we have brought up a new framework in the second study, which considers both the interactions between oil and CO2 and the interactions with the pore wall. Given the high computational costs, a machine learning model is trained with the data collected to make future predictions faster and cheaper. The third study quantifies the strength of a new type of flow. This flow can be comparable in magnitude to pressure difference-driven flow in tiny pores. Lastly, the recovery of an oil mixture composed of light and heavy hydrocarbons is explored. It was discovered that gas injection not only increases the overall oil recovery rate but also decreases the selectivity toward lighter hydrocarbons. These discoveries pave the way for improved models and strategies to optimize the gas injection process to recover oil from these challenging reservoirs, ultimately meeting the energy needs while supporting efforts to reduce atmospheric CO2 levels.