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Imageamento da porosidade através de perfis geofísicos de poçoMIRANDA, Anna Ilcéa Fischetti 27 January 2004 (has links)
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Previous issue date: 2004 / CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico / O imageamento da porosidade é uma representação gráfica da distribuição lateral da
porosidade da rocha, estimada a partir de dados de perfis geofísicos de poço. Apresenta-se aqui
uma metodologia para produzir esta imagem geológica, totalmente independente da intervenção
do intérprete, através de um algoritmo, dito, interpretativo baseado em dois tipos de redes neurais
artificiais. A primeira parte do algoritmo baseia-se em uma rede neural com camada competitiva
e é construído para realizar uma interpretação automática do clássico gráfico o Pb - ΦN, produzindo
um zoneamento do perfil e a estimativa da porosidade. A segunda parte baseia-se em uma rede
neural com função de base radial, projetado para realizar uma integração espacial dos dados, a
qual pode ser dividida em duas etapas. A primeira etapa refere-se à correlação de perfis de poço e
a segunda à produção de uma estimativa da distribuição lateral da porosidade. Esta metodologia ajudará o intérprete na definição do modelo geológico do reservatório e,
talvez o mais importante, o ajudará a desenvolver de um modo mais eficiente as estratégias para o
desenvolvimento dos campos de óleo e gás. Os resultados ou as imagens da porosidade são
bastante similares às seções geológicas convencionais, especialmente em um ambiente
deposicional simples dominado por clásticos, onde um mapa de cores, escalonado em unidades
de porosidade aparente para as argilas e efetiva para os arenitos, mostra a variação da porosidade
e a disposição geométrica das camadas geológicas ao longo da seção. Esta metodologia é aplicada em dados reais da Formação Lagunillas, na Bacia do Lago
Maracaibo, Venezuela. / Porosity images are graphical representations of the lateral distribution of rock porosity
estimated from well log data. We present a methodology to produce this geological image
entirely independent of interpreter intervention, with an interpretative algorithm approach, which
is based on two types of artificial neural networks. The first is based on neural competitive layer
and is constructed to perform an automatic interpretation of the classical Pb - ΦN cross-plot,
which produces the log zonation and porosity estimation. The second is a feed-forward neural
network with radial basis function designed to perform a spatial data integration, which can be
divided in two steps. The first refers to well log correlation and the second produces the
estimation of lateral porosity distribution. This methodology should aid the interpreter in defining the reservoir geological model,
and, perhaps more importantly, it should help him to efficiently develop strategies for oil or gas
field development. The results or porosity images are very similar to conventional geological
cross-sections, especially in a depositional setting dominated by clastics, where a color map
scaled in porosity units illustrates the porosity distribution and the geometric disposition of
geological layers along the section. The methodology is applied over actual well log data from the Lagunillas Formation, in
the Lake Maracaibo basin, located in western Venezuela.
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Study of dialogic approaches and responses in planning low-income communities in Maracaibo, Venezuela : the "Promotion of Full Citizenship" planRincon, Hugo Rodolfo, 1968- 22 March 2011 (has links)
The research followed up a local development initiative in Maracaibo, Venezuela, named Programa Promoción de la Ciudadanía Plena (Promotion of Full Citizenship Program), a joint initiative that has sought to bring the population of low-income communities to the sphere of citizen participation with a revaluation of citizenship and the promotion of participation. The research included first, a preliminary bibliographical review of the theoretical framework to understand the significance of citizenship and participation at the community level and the implications of organizational development and self-improvement approaches in development projects and institutions, and second, the review of the principles of the local program and the social-economic data of the four communities considered in the study. The results of a preliminary survey (secondary data provided by the municipality) of adult heads of household from the four communities, who openly expressed to the institutions their interest in participating and benefiting from the program, and the passive observation of local meetings and workshops in the communities contributed to the analysis. A series of open-ended interviews to facilitators (3 individuals) were conducted in 2006 in order to assess the facilitator's identification with the program's objectives and the possible bond between the learning assumptions and their personal experiences while working in these communities. That same year, a final series of open-ended interviews to a sample group of 39 beneficiaries (30% of the group that successfully completed the citizenship and technical education), provided the input to assess the impact of the program in the motivation of people toward participation and self-improvement. In these events, information was extracted, which contributed to the evaluation of people's expectations and attitudes, as they differed or not from the initial condition. A methodological guideline, in the form of field notes and questionnaires, was needed to address and manage conversation and dialogue. Following an interpretive and constructivist approach, evidence was inferred from the logic of the narratives gathered in meetings and interviews, and a coded frequency of responses. Findings suggest that the initiative strengthened local people's empowerment by involving them in the collaborative identification of problems and issues affecting their lives, in all activities planned to tie the relationship among stakeholders, and in every recognition and public ceremony. People's improvement depended on economic growth, but it was necessary that beneficiaries develop and exercise their capacities, abilities, knowledge, information and motivation, which were necessary conditions to improve the quality of life of local residents, and consequently, to strengthen the local social capital. Project agents did it with a respectful dialogue in the decision-making concerning the design and construction proposal, and recognizing people's own capacities, which assured collaboration and feedback. People did not participate unless they believed that an interest or individual benefit was possible; and for them, the immediate interest was economic. People associated changes to the following values --from high to low frequency of response: being more confident, reaching mutual support, improving communication, strengthening unity, consciousness, and achieving better social relations. Empowerment of the individual as head of household was strengthened by his or her involvement in the collaborative identification of household limitations and housing-related issues. Nevertheless, beyond the individual and household levels, the success of the educational strategy was not sufficiently effective to reach changes on people's attitude and motivation to confront and interact in the solution of community-related issues, but the increase of 6 percent in this indicator indicated that change was possible but required the sustainability of the educational approach in the communities. By the time the field research ended, a perceivable empowerment and partnership approach, with all the complex administrative and intellectual assumptions, guided Ciudadanía Plena toward its set goals. The attention and dedication in the four barrios were based on the need to materialize an ideal that was expected to expand in order to reach more communities in the near future. The transparency, the material incentive and the citizenship education to achieve self-improvement and empowerment were key elements to achieve change and improvement. / text
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Determinação automática da porosidade e zoneamento de perfis através da rede neural artificial competitivaLIMA, Klédson Tomaso Pereira de January 2000 (has links)
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Previous issue date: 2000 / CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico / Duas das mais importantes atividades da interpretação de perfis para avaliação de reservatórios de hidrocarbonetos são o zoneamento do perfil (log zonation) e o cálculo da porosidade efetiva das rochas atravessadas pelo poço. O zoneamento é a interpretação visual do perfil para identificação das camadas reservatório e, consequentemente, dos seus limites verticais, ou seja, é a separação formal do perfil em rochas reservatório e rochas selante. Todo procedimento de zoneamento é realizado de forma manual, valendo-se do conhecimento geológico-geofísico e da experiência do intérprete, na avaliação visual dos padrões (características da curva do perfil representativa de um evento geológico) correspondentes a cada tipo litológico específico. O cálculo da porosidade efetiva combina tanto uma atividade visual, na identificação dos pontos representativos de uma particular rocha reservatório no perfil, como a escolha adequada da equação petrofísica que relaciona as propriedades físicas mensuradas da rocha com sua porosidade. A partir do conhecimento da porosidade, será estabelecido o volume eventualmente ocupado por hidrocarboneto. Esta atividade, essencial para a qualificação de reservatórios, requer muito do conhecimento e da experiência do intérprete de perfil para a efetiva avaliação da porosidade efetiva, ou seja, a porosidade da rocha reservatório, isenta do efeito da argila sobre a medida das propriedades físicas da mesma. Uma forma eficiente de automatizar estes procedimentos e auxiliar o geofísico de poço nestas atividades, que particularmente demandam grande dispêndio de tempo, é apresentado nesta dissertação, na forma de um novo perfil, derivado dos perfis tradicionais de porosidade, que apresenta diretamente o zoneamento. Pode-se destacar neste novo perfil as profundidades do topo e da base das rochas reservatório e das rochas selante, escalonado na forma de porosidade efetiva, denominado perfil de porosidade efetiva zoneado. A obtenção do perfil de porosidade efetiva zoneado é baseado no projeto e execução de várias arquiteturas de rede neural artificial, do tipo direta, com treinamento não supervisionado e contendo uma camada de neurônios artificiais, do tipo competitivo. Estas arquiteturas são projetadas de modo a simular o comportamento do intérprete de perfil, quando da utilização do gráfico densidade-neutrônico, para as situações de aplicabilidade do modelo arenito-folhelho. A aplicabilidade e limitações desta metodologia são avaliadas diretamente sobre dados reais, oriundos da bacia do Lago Maracaibo (Venezuela). / Two of the most important activities of log interpretation, for the evaluation of hydrocarbon reservoirs are the log zonation and the effective porosity calculation of the rocks crossed by the well. The log zonation is the visual log interpretation for the identification, in depth, of the reservoir layers and its vertical limits, that is to say, it is the formal separation in reservoir rocks and non reservoir rocks (shales). The log zonation procedure is accomplished in a manual way, being been worth of the geologic and geophysical knowledge, and of the experience of the log analyst, in the visual evaluation of the curve patterns (log characteristics) corresponding to each specific rock type. The calculation of the effective porosity (porosity of the rock reservoir corrected by clay effects), combines a visual activity so much in the identification of the representative points of a reservoir rock in the log, as well as the adapted choice of the petrophysics equation, that relates the physical properties of the rock to the porosity. Starting from the knowledge of the porosity, the hydrocarbon volume will be established. This activity, essential for the reservoirs qualification, requests a lot of the knowledge and of the experience of the log analyst, for the effective porosity evaluation. An efficient form of automating these procedures and assistant the log analyst, in these activities, that particularly demand a great expenditure of time, is presented in this dissertation, in the form of a new log, derived of the traditional porosity logs, that presents the log zonation, highlighting the top and base depths of the occurrences of reservoir rocks, and non reservoir rocks, scaled in form of effective porosity, called here, as "zoning effective porosity log". The obtaining of the zoning effective porosity log, is based on the project and execution of several architectures of artificial neural feedforward networks, with not supervised training, and contends a layer of artificial competitive neurons. Projected in way to simulate the behavior of the log analyst, when he uses the neutron-density chart, for the situations of applicability of the shale-sandstone model. The applicability and limitations of this methodology will be appraised on real data, originated from of Lago Maracaibo's basin (Venezuela).
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