Made available in DSpace on 2014-12-17T14:08:51Z (GMT). No. of bitstreams: 1 DeboraCMP_DISSERT_Pre-textuais.pdf: 440461 bytes, checksum: de18053fd5097e8172e698a19f80a5e7 (MD5) Previous issue date: 2012-03-30 / Produced water is characterized as one of the most common wastes generated during exploration and production of oil. This work aims to develop methodologies based on comparative statistical processes of hydrogeochemical analysis of production zones in order to minimize types of high-cost interventions to perform identification test fluids - TIF. For the study, 27 samples were collected from five different production zones were measured a total of 50 chemical species. After the chemical analysis was applied the statistical data, using the R Statistical Software, version 2.11.1. Statistical analysis was performed in three steps. In the first stage, the objective was to investigate the behavior of chemical species under study in each area of production through the descriptive graphical analysis. The second step was to identify a function that classify production zones from each sample, using discriminant analysis. In the training stage, the rate of correct classification function of discriminant analysis was 85.19%. The next stage of processing of the data used for Principal Component Analysis, by reducing the number of variables obtained from the linear combination of chemical species, try to improve the discriminant function obtained in the second stage and increase the discrimination power of the data, but the result was not satisfactory. In Profile Analysis curves were obtained for each production area, based on the characteristics of the chemical species present in each zone. With this study it was possible to develop a method using hydrochemistry and statistical analysis that can be used to distinguish the water produced in mature fields of oil, so that it is possible to identify the zone of production that is contributing to the excessive elevation of the water volume. / A ?gua produzida caracteriza-se como um dos res?duos mais comuns gerados durante as fases de explora??o e produ??o de petr?leo. Este trabalho tem como objetivo desenvolver metodologias baseadas em processos estat?stico-comparativos de an?lises hidrogeoqu?micas de zonas de produ??o com o objetivo de minimizar tipos de interven??es de altos custos para realiza??o de teste de identifica??o de fluidos TIF. Para o estudo, foram coletadas 27 amostras de cinco zonas de produ??o diferentes e foram medidos um total de 50 esp?cies qu?micas. Ap?s as an?lises qu?micas foi aplicado o tratamento estat?stico aos dados, utilizando o Software Estat?stico R, vers?o 2.11.1. O tratamento estat?stico foi realizado em tr?s etapas. Na primeira etapa, o objetivo foi verificar o comportamento das esp?cies qu?micas em estudo em cada zona de produ??o atrav?s da an?lise gr?fica descritiva. A segunda etapa consistiu em identificar uma fun??o que classificasse as zonas de produ??o de cada amostra, utilizando An?lise Discriminante. Na etapa de treinamento, a taxa de acerto de classifica??o da fun??o da an?lise discriminante foi de 85,19%. A etapa seguinte do tratamento estat?stico dos dados utilizou An?lise de Componentes Principais para, atrav?s da redu??o do n?mero de vari?veis obtidas a partir da combina??o linear das esp?cies qu?micas, tentar melhorar a fun??o discriminante obtida na segunda etapa e aumentar o poder de discrimina??o dos dados, por?m o resultado n?o foi satisfat?rio. Na An?lise de Perfis foram obtidas curvas para cada zona de produ??o, baseadas nas caracter?sticas das esp?cies qu?micas presentes em cada zona. Com este trabalho foi poss?vel desenvolver uma metodologia utilizando a hidroqu?mica e a an?lise estat?stica que pode ser utilizada para distinguir a ?gua produzida em campos maduros de petr?leo, de forma que seja poss?vel identificar a zona de produ??o que est? contribuindo para a eleva??o excessiva do volume de ?gua.

Made available in DSpace on 2014-12-17T14:55:03Z (GMT). No. of bitstreams: 1 IloneideCOR.pdf: 1010601 bytes, checksum: 76bbc04aa0a456f079121fb0d750ea74 (MD5) Previous issue date: 2005-03-03 / The problems of combinatory optimization have involved a large number of researchers in search of approximative solutions for them, since it is generally accepted that they are unsolvable in polynomial time. Initially, these solutions were focused on heuristics. Currently, metaheuristics are used more for this task, especially those based on evolutionary algorithms. The two main contributions of this work are: the creation of what is called an -Operon- heuristic, for the construction of the information chains necessary for the implementation of transgenetic (evolutionary) algorithms, mainly using statistical methodology - the Cluster Analysis and the Principal Component Analysis; and the utilization of statistical analyses that are adequate for the evaluation of the performance of the algorithms that are developed to solve these problems. The aim of the Operon is to construct good quality dynamic information chains to promote an -intelligent- search in the space of solutions. The Traveling Salesman Problem (TSP) is intended for applications based on a transgenetic algorithmic known as ProtoG. A strategy is also proposed for the renovation of part of the chromosome population indicated by adopting a minimum limit in the coefficient of variation of the adequation function of the individuals, with calculations based on the population. Statistical methodology is used for the evaluation of the performance of four algorithms, as follows: the proposed ProtoG, two memetic algorithms and a Simulated Annealing algorithm. Three performance analyses of these algorithms are proposed. The first is accomplished through the Logistic Regression, based on the probability of finding an optimal solution for a TSP instance by the algorithm being tested. The second is accomplished through Survival Analysis, based on a probability of the time observed for its execution until an optimal solution is achieved. The third is accomplished by means of a non-parametric Analysis of Variance, considering the Percent Error of the Solution (PES) obtained by the percentage in which the solution found exceeds the best solution available in the literature. Six experiments have been conducted applied to sixty-one instances of Euclidean TSP with sizes of up to 1,655 cities. The first two experiments deal with the adjustments of four parameters used in the ProtoG algorithm in an attempt to improve its performance. The last four have been undertaken to evaluate the performance of the ProtoG in comparison to the three algorithms adopted. For these sixty-one instances, it has been concluded on the grounds of statistical tests that there is evidence that the ProtoG performs better than these three algorithms in fifty instances. In addition, for the thirty-six instances considered in the last three trials in which the performance of the algorithms was evaluated through PES, it was observed that the PES average obtained with the ProtoG was less than 1% in almost half of these instances, having reached the greatest average for one instance of 1,173 cities, with an PES average equal to 3.52%. Therefore, the ProtoG can be considered a competitive algorithm for solving the TSP, since it is not rare in the literature find PESs averages greater than 10% to be reported for instances of this size. / Os problemas de otimiza??o combinat?ria t?m envolvido um grande n?mero de pesquisadores na busca por solu??es aproximativas para aqueles, desde a aceita??o de que eles s?o considerados insol?veis em tempo polinomial. Inicialmente, essas solu??es eram focalizadas por meio de heur?sticas. Atualmente, as metaheur?sticas s?o mais utilizadas para essa tarefa, especialmente aquelas baseadas em algoritmos evolucion?rios. As duas principais contribui??es deste trabalho s?o: a cria??o de uma heur?stica, denominada Operon, para a constru??o de cadeias de informa??es necess?rias ? implementa??o de algoritmos transgen?ticos (evolucion?rios) utilizando, principalmente, a metodologia estat?stica - An?lise de Agrupamentos e An?lise de Componentes Principais -; e a utiliza??o de an?lises estat?sticas adequadas ? avalia??o da performance de algoritmos destinados ? solu??o desses problemas. O Operon visa construir, de forma din?mica e de boa qualidade, cadeias de informa??es a fim de promover uma busca -inteligente- no espa?o de solu??es. O Problema do Caixeiro Viajante (PCV) ? focalizado para as aplica??es que s?o realizadas com base num algoritmo transgen?tico, denominado ProtoG. Prop?e-se, tamb?m, uma estrat?gia de renova??o de parte da popula??o de cromossomos indicada pela ado??o de um limite m?nimo no coeficiente de varia??o da fun??o de adequa??o dos indiv?duos, calculado com base na popula??o. S?o propostas tr?s an?lises estat?sticas para avaliar a performance de algoritmos. A primeira ? realizada atrav?s da An?lise de Regress?o Log?stica, com base na probabilidade de obten??o da solu??o ?tima de uma inst?ncia do PCV pelo algoritmo em teste. A segunda ? realizada atrav?s da An?lise de Sobreviv?ncia, com base numa probabilidade envolvendo o tempo de execu??o observado at? que a solu??o ?tima seja obtida. A terceira ? realizada por meio da An?lise de Vari?ncia n?o param?trica, considerando o Erro Percentual da Solu??o (EPS) obtido pela percentagem em que a solu??o encontrada excede a melhor solu??o dispon?vel na literatura. Utiliza-se essa metodologia para a avalia??o da performance de quatro algoritmos, a saber: o ProtoG proposto, dois algoritmos mem?ticos e um algoritmo Simulated Annealing. Foram realizados seis experimentos, aplicados a sessenta e uma inst?ncias do PCV euclidiano, com tamanhos de at? 1.655 cidades. Os dois primeiros experimentos tratam do ajuste de quatro par?metros utilizados no algoritmo ProtoG, visando melhorar a performance do mesmo. Os quatro ?ltimos s?o utilizados para avaliar a performance do ProtoG em compara??o aos tr?s algoritmos adotados. Para essas sessenta e uma inst?ncias, conclui-se, sob testes estat?sticos, que h? evid?ncias de que o ProtoG ? superior a esses tr?s algoritmos em cinq?enta inst?ncias. Al?m disso, para as trinta e seis inst?ncias consideradas nos tr?s ?ltimos experimentos, nos quais a avalia??o da performance dos algoritmos foi realizada com base no EPS, observou-se que o ProtoG obteve EPSs m?dios menores que 1% em quase metade das inst?ncias, tendo atingido a maior m?dia para uma inst?ncia composta por 1.173 cidades, com EPS m?dio igual a 3,52%. Logo, o ProtoG pode ser considerado um algoritmo competitivo para solucionar o PCV, pois n?o ? raro serem reportados, na literatura, EPSs m?dios maiores que 10% para inst?ncias desse porte.

Made available in DSpace on 2014-12-17T15:42:31Z (GMT). No. of bitstreams: 1 MariaFGM.pdf: 2684798 bytes, checksum: 4d672e17bab00bdd5d88eb70b9c57edf (MD5) Previous issue date: 2007-03-30 / Petr?leo Brasileiro SA - PETROBRAS / Many studies on environmental ecosystems quality related to polycyclic aromatic hydrocarbons (PAH) have been carried out routinely due to their ubiquotus presence worldwide and to their potential toxicity after its biotransformation. PAH may be introduced into the environmet by natural and anthropogenic processes from direct runoff and discharges and indirect atmospheric deposition. Sources of naturally occurring PAHs include natural fires, natural oil seepage and recent biological or diagenetic processes. Anthropogenic sources of PAHs, acute or chronic, are combustion of organic matter (petroleum, coal, wood), waste and releases/spills of petroleum and derivatives (river runoff, sewage outfalls, maritime transport, pipelines). Besides the co-existence of multiples sources of PAH in the environmental samples, these compounds are subject to many processes that lead to geochemical fates (physical-chemical transformation, biodegradation and photo-oxidation), which leads to an alteration of their composition. All these facts make the identification of the hydrocarbons sources, if petrogenic, pyrolytic or natural, a challenge. One of the objectives of this study is to establish tools to identify the origin of hydrocarbons in environmental samples. PAH diagnostic ratios and PAH principal component analysis were tested on a critical area: Guanabara Bay sediments. Guanabara Bay is located in a complex urban area of Rio de Janeiro with a high anthropogenic influence, being an endpoint of chronic pollution from the Greater Rio and it was the scenario of an acute event of oil release in January 2000. It were quantified 38 compounds, parental and alkylated PAH, in 21 sediment samples collected in two surveys: 2000 and 2003. The PAH levels varied from 400 to 58439 ng g-1. Both tested techniques for origin identification of hydrocarbons have shown their applicability, being able to discriminate the PAH sources for the majority of the samples analysed. The bay sediments were separated into two big clusters: sediments with a clear pattern of petrogenic introduction of hydrocarbons (from intertidal area) and sediments with combustion characteristics (from subtidal region). Only a minority of the samples could not display a clear contribution of petrogenic or pyrolytic input. The diagnostic ratios that have exhibited high ability to distinguish combustion- and petroleum-derived PAH inputs for Guanabara Bay sediments were Phenanthrene+Anthracene/(Phenanthrene+Anthracene+C1Phenanthrene); Fluorantene/(Fluorantene+Pyrene); Σ (other 3-6 ring PAHs)/ Σ (5 alkylated PAH series). The PCA results prooved to be a useful tool for PAH source identification in the environment, corroborating the diagnostic indexes. In relation to the temporal evaluation carried out in this study, it was not verified significant changes on the class of predominant source of the samples. This result indicates that the hydrocarbons present in the Guanabara Bay sediments are mainly related to the long-term anthropogenic input and not directly related to acute events such as the oil spill of January 2000. This findings were similar to various international estuarine sites. Finally, this work had a complementary objective of evaluating the level of hydrocarbons exposure of the aquatic organisms of Guanabara Bay. It was a preliminary study in which a quantification of 12 individual biliar metabolites of PAH was performed in four demersal fish representing three different families. The analysed metabolites were 1-hydroxynaphtalene, 2-hidroxinaphtalene, 1hydroxyphenanthrene, 9-hydroxyphenanthrene, 2-hydroxyphenanthrene, 1hydroxypyrene, 3-hidroxibiphenil, 3- hydroxyphenanthrene, 1-hydroxychrysene, 9hydroxyfluorene, 4-hydroxyphenanthrene, 3-hydroxybenz(a)pyrene. The metabolites concentrations were found to be high, ranging from 13 to 177 ?g g-1, however they were similar to worldwide regions under high anthropogenic input. Besides the metabolites established by the used protocol, it was possible to verified high concentrations of three other compounds not yet reported in the literature. They were related to pyrolytic PAH contribution to Guanabara Bay aquatic biota: 1-hydroxypyrine and 3-hydroxybenz(a)pyrine isomers / In?meros estudos da qualidade de ecossistemas naturais em rela??o a contamina??o de hidrocarbonetos polic?ciclos arom?ticos (HPA) t?m sido desenvolvidos continuadamente face a sua presen?a ub?quoa em todo o planeta e ao seu potencial t?xico ap?s a biotransforma??o. A introdu??o dos HPA no meio ambiente pode ocorrer atrav?s de processos naturais e antropog?nicos, atrav?s de despejos e/ou drenagens e deposi??o atmosf?rica indireta. Fontes naturais de HPA incluem queimadas naturais, exsuda??es de ?leo e processos biog?nicos recentes. Fontes antropog?nicas de HPA, advindas de eventos cr?nicos ou agudos, s?o a combust?o incompleta de ?leo combust?vel automotivo e industrial, a queima intencional de madeira e planta??es, os despejos dom?sticos e industriais, as drenagens pluviais urbanas, os efluentes da ind?stria petrol?fera, os derrames acidentais de ?leo e derivados. Al?m da coexist?ncia de m?ltiplas fontes destes hidrocarbonetos nas amostras ambientais, os HPA est?o sujeitos a v?rios processos geoqu?micos que conduzem ? altera??o de sua composi??o qu?mica ao longo do tempo, tornando a identifica??o das fontes contaminantes, se petrog?nica, pirol?tica ou natural, um verdadeiro desafio. Desta forma, um dos objetivos deste estudo foi estabelecer ferramentas que possibilitem a determina??o das fontes de hidrocarbonetos no meio ambiente. Foram utilizadas raz?es diagn?sticas e an?lise de componentes principais de HPA, tendo sido quantificados 38 compostos, incluindo os HPA parentais e alquilados, em 21 amostras de sedimento da Ba?a de Guanabara, coletadas nos anos de 2000 e 2003. A Ba?a de Guanabara ? um ecossistema estuarino com elevada influ?ncia antropog?nica, que recebe polui??o cr?nica da regi?o metropolitana do Rio de Janeiro e que foi cen?rio de um derrame de ?leo em janeiro de 2000. As concentra??es de HPA nos sedimentos estudados apresentaram-se na faixa de 400 a 58439 ng g-1. Ambas as t?cnicas de diferencia??o de fontes de HPA testadas, raz?es diagn?sticas e an?lise de componentes principais, demonstraram sua aplicabilidade, permitindo a diferencia??o das fontes de HPA para a maioria dos sedimentos da ba?a, que foram divididos em dois grandes grupos: sedimentos com padr?es de introdu??o de hidrocarbonetos predominantemente petrog?nicos e sedimentos com caracter?sticas de combust?o. Apenas uma minoria de amostras n?o apresentou com nitidez a natureza de sua contamina??o. As raz?es que apresentaram maior capacidade em diferenciar as fontes de HPA foram Fluoranteno / (Fluoranteno + Pireno), (Fenantreno + Antraceno) / (Fenantreno + Antraceno + C1Fenantreno) e o ?ndice pirol?tico, Σ (HPA parentais de 3-6 an?is) /Σ (5 s?ries de HPA alquilados). Na avalia??o temporal realizada neste estudo n?o foram verificadas varia??es significativas na natureza das fontes contaminantes predominantes na ba?a, revelando que os hidrocarbonetos presentes est?o correlacionados principalmente com os aportes cr?nicos e n?o diretamente com eventos agudos como o derrame de ?leo ocorrido em janeiro de 2000. Este estudo teve como segundo objetivo a avalia??o preliminar do n?vel de exposi??o a que os organismos aqu?ticos da Ba?a de Guanabara est?o submetidos, atrav?s da quantifica??o de 12 metab?litos individuais de HPA presentes em bile de peixe de quatro esp?cies demersais representativas de tr?s fam?lias diferentes. Os metab?litos analisados foram 1-hidroxinaftaleno, 1-hidroxifenantreno, 9hidroxifenantreno, 2-hidroxinaftaleno, 2-hidroxifenantreno, 1-hidroxipireno, 3hidroxibifenila, 3-hidroxifenantreno, 1-hidroxicriseno, 9-hidroxifluoreno, 4hidroxifenantreno, 3-hidroxibenzo(a)pireno. As concentra??es encontradas nas esp?cies de peixes analisadas mostraram-se elevadas, na faixa de 13 a 177 ?g g1, por?m similares ?s encontradas em algumas regi?es de grande influ?ncia antropog?nica, tanto no Brasil quanto no exterior. Al?m dos metab?litos estabelecidos pela metodologia utilizada, foi poss?vel quantificar tr?s compostos, ainda n?o reportados na literatura, em concentra??es relevantes. Estes metab?litos, relacionados a contribui??o pirol?tica de HPA aos organismos aqu?ticos da Ba?a de Guanabara, s?o is?meros de 1-hidroxipireno e de 3-hidroxibenzo(a)pireno