Detalhes bibliográficos
Ano de defesa: |
2012 |
Autor(a) principal: |
Pires, Paulo Roberto da Motta |
Orientador(a): |
Dória Neto, Adrião Duarte |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Federal do Rio Grande do Norte
|
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciência e Engenharia do Petróleo
|
Departamento: |
Pesquisa e Desenvolvimento em Ciência e Engenharia de Petróleo
|
País: |
BR
|
Palavras-chave em Português: |
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Palavras-chave em Inglês: |
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Área do conhecimento CNPq: |
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Link de acesso: |
https://repositorio.ufrn.br/jspui/handle/123456789/12970
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Resumo: |
Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization |