TRABALHOS DE FIM DE CURSO @PUC-Rio
| Título: | ESTIMATION OF WELL PRODUCTION FLOW RATE USING ARTIFICIAL INTELLIGENCE TECHNIQUES | ||||||||||||
| Autor(es): |
RAFAEL BASTOS SCISINIO DIAS |
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| Colaborador(es): |
MARCIO DA SILVEIRA CARVALHO - Orientador SERGIO SANTIAGO RIBEIRO - Coorientador |
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| Catalogação: | 12/JUL/2022 | Língua(s): | PORTUGUESE - BRAZIL |
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| Tipo: | TEXT | Subtipo: | SENIOR PROJECT | ||||||||||
| Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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| Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=59936@1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=59936@2 |
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| DOI: | https://doi.org/10.17771/PUCRio.acad.59936 | ||||||||||||
| Resumo: | |||||||||||||
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The use of artificial intelligence techniques to estimate the production flow rate of wells has been applied as a substitute for the traditional methods of well characterization. However, it is not clear that artificial intelligence techniques are able to actually provide an estimate of the production flow, with a reduced error. Thus, the objective of this work is to develop a methodology and a computational code capable of estimating the production flow, with a low error. To achieve the objective, some simulations were carried out with different models of neural network and the generated predictions were compared with the real data. And the results obtained showed satisfactory behavior, as well as a considerably reduced error.
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