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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Modelagem matem?tica e experimental da perda de injetividade em po?os canhoneados

Gomes, Vanessa Limeira Azevedo 20 November 2015 (has links)
Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-06-10T19:20:11Z No. of bitstreams: 1 VanessaLimeiraAzevedoGomes_TESE.pdf: 3568027 bytes, checksum: 5b81da1eba84c90799bbf4cc69a3c6c1 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-06-13T20:36:35Z (GMT) No. of bitstreams: 1 VanessaLimeiraAzevedoGomes_TESE.pdf: 3568027 bytes, checksum: 5b81da1eba84c90799bbf4cc69a3c6c1 (MD5) / Made available in DSpace on 2016-06-13T20:36:35Z (GMT). No. of bitstreams: 1 VanessaLimeiraAzevedoGomes_TESE.pdf: 3568027 bytes, checksum: 5b81da1eba84c90799bbf4cc69a3c6c1 (MD5) Previous issue date: 2015-11-20 / Ag?ncia Nacional do Petr?leo - ANP / A inje??o de ?gua em reservat?rios de petr?leo ? uma t?cnica de recupera??o amplamente utilizada para a recupera??o de ?leo. No entanto, a ?gua injetada cont?m part?culas suspensas que podem ser retidas, causando dano ? forma??o e perda de injetividade. Nesses casos, ? necess?rio estimular a forma??o danificada com o intuito de restaurar a injetividade dos po?os injetores. A perda de injetividade causa um grande impacto negativo ? economia de produ??o de petr?leo e, por isso, prever a injetividade ? importante para o gerenciamento de projetos de inje??o de ?gua. Modelos matem?ticos para perda de injetividade permitem estudar o efeito da qualidade da ?gua injetada bem como das caracter?sticas do po?o e da forma??o. Dessa forma, foi desenvolvido um modelo matem?tico da perda de injetividade para po?os injetores canhoneados. A novidade cient?fica deste trabalho refere-se ? modelagem e previs?o da perda de injetividade em po?os canhoneados injetores, considerando a filtra??o profunda e forma??o do reboco externo em canhoneados esferoidais. A modelagem cl?ssica para a filtra??o profunda foi reescrita em coordenadas esferoidais. A solu??o para a concentra??o de part?culas em suspens?o foi obtida analiticamente e a concentra??o de part?culas retidas, que causam dano ? forma??o, foi resolvida numericamente. Considerando uma vaz?o injetada constante e utilizando a lei de Darcy modificada, estimamos a imped?ncia, definida como sendo o inverso da injetividade normalizada pelo inverso da injetividade inicial. Finalmente, foram realizados testes de injetividade cl?ssicos para fluxo linear, em amostras de Arenito Berea, e tamb?m em amostras "canhoneadas". Os par?metros do modelo, coeficientes de filtra??o e de dano ? forma??o, obtidos a partir do tratamento dos dados, foram utilizados para a verifica??o da modelagem proposta. As simula??es mostraram um bom ajuste aos dados experimentais, sendo observado que a raz?o entre o tamanho das part?culas e dos poros tem grande influ?ncia no comportamento da perda de injetividade. / Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy?s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.
2

Modelagem e previs?o da perda de injetividade em po?os canhoneados

Gomes, Vanessa Limeira Azevedo 20 August 2010 (has links)
Made available in DSpace on 2014-12-17T14:08:40Z (GMT). No. of bitstreams: 1 VanessaLAG_DISSERT.pdf: 1481281 bytes, checksum: 8b61d326c9b0fb24441950affcfa1205 (MD5) Previous issue date: 2010-08-20 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells / A inje??o de ?gua ? uma t?cnica amplamente utilizada para deslocar o ?leo em dire??o aos po?os produtores e manter a press?o em reservat?rios de petr?leo. Entretanto, part?culas suspensas na ?gua injetada podem ser retidas no meio poroso, causando dano ? forma??o (redu??o de permeabilidade) e perda de injetividade. Quando ocorre essa redu??o de injetividade ? necess?rio aumentar a press?o de inje??o para manter a vaz?o de ?gua injetada. Desse modo, a correta previs?o da perda de injetividade ? essencial em projetos de inje??o de ?gua. Neste trabalho, um simulador, baseado no modelo tradicional da filtra??o em meios porosos (incluindo filtra??o profunda e forma??o do reboco externo), foi desenvolvido e aplicado para prever a perda de injetividade em po?os canhoneados (tal previs?o foi feita a partir de dados de hist?rico). Al?m disso, tamb?m foi discutida a determina??o experimental dos coeficientes do modelo e a perda de injetividade em po?os abertos. A modelagem da injetividade apresentou bom ajuste aos dados de campo, podendo ser utilizada para auxiliar no planejamento de estimula??es de po?os injetores
3

An?lise da modelagem experimental da perda de injetividade

Bonato, Adriano Jos? do Amaral Mello 13 July 2012 (has links)
Made available in DSpace on 2014-12-17T14:08:53Z (GMT). No. of bitstreams: 1 AdrianoJAMB_DISSERT.pdf: 6352547 bytes, checksum: 4f7f1e181e2f04659c084a8901764e58 (MD5) Previous issue date: 2012-07-13 / Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different / A perda de injetividade, que pode ser causada pela reten??o de part?culas, ocorre geralmente durante a inje??o ou reinje??o de ?gua em campos de petr?leo. V?rios mecanismos, incluindo a exclus?o pelo tamanho (straining), s?o respons?veis pela reten??o de part?culas e bloqueio dos poros da forma??o, causando dano e o decl?nio da injetividade. A previs?o para o dano ? forma??o e a queda da injetividade ? essencial para o gerenciamento de projetos de inje??o de ?gua. O modelo cl?ssico (MC), que incorpora os coeficientes de filtra??o e de dano ? forma??o, tem sido amplamente utilizado na previs?o da perda de injetividade. Esse modelo apresenta bons resultados quando apenas um mecanismo de reten??o ? atuante. Entretanto, v?rios autores relataram discrep?ncias significativas entre o modelo cl?ssico e os dados experimentais, motivando o desenvolvimento de modelos que consideram m?ltiplos mecanismos de reten??o de part?culas, como o modelo de Santos e Barros (MSB, 2010). Neste trabalho, foi estudada a solu??o do problema inverso para diferentes modelos. A partir deste estudo, foi desenvolvido um software para o tratamento dos dados experimentais. Finalmente, os dados experimentais foram ajustados usando tanto o MC quanto o MSB. Os resultados demonstraram que, dependendo da fun??o dano ? forma??o utilizada, as previs?es dos modelos MC e MSB para a perda de injetividade podem ser significativamente diferentes

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