Artificial neural network applied to the pore pressure estimation of a rocky formation
DOI:
https://doi.org/10.11606/issn.2316-9095.v21-163305Keywords:
Artificial intelligence, Drilling, Eaton MethodAbstract
Well planning is one of the most important steps of drilling engineering to avoid problems such as kicks, well instability, blowouts, and lost circulation, which represents the main causes of environmental damage, economic loss, and human loss included. These damages are especially critical when it comes to ultra-deepwater drilling. Usually, to estimate pore pressure, methods based on historical experience, mathematical statistical, empirical, and field-measured are used. However, accuracy on each method is a challenge for improvement, as they depend on how the instrument or petrophysics analysts reads the particular measurement. Therefore, methods such as artificial neural network (ANN) are studied, aiming to find values of formation pressures with lesser margin of error. Besides being a faster and more accurate method than the conventional ones, the ANN is an adaptive computer system inspired by the human brain itself, that acquires knowledge with experience. The outline is to use this artificial intelligence to estimate pore pressure. Therewith, a case study was performed to create, train, and implement ANN from data logs of the well studied, besides depth and density of rock formation information. The proposal is to estimate pore pressure using this artificial intelligence technique and compare the obtained results between the Eaton conventional method and the created ANN, in order to prove that the results using this new technique reach smaller errors.
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References
Aadnoy, B., Looyeh, R. (2014). Mecânica de rochas aplicada. Rio de Janeiro: Elsevier.
Cai, Z., Zhang, H., Li, J., Zheng, J., Yu, Q., Liu, K., Liu, Y. (2018). New Technology to assist drilling to improve drilling rate in unconventional gas resources: pulsed arc plasma shockwave technology. Abu Dhabi International Petroleum Exhibition and Conference. Abu Dhabi. https://doi.org/10.2118/193279-MS
Domingues, F. C. P. (2016). Aplicação de um projeto de perfuração para um poço marítimo. Trabalho de Conclusão de Curso. Niterói: Departamento de Engenharia Química e de Petróleo – UFF. Disponível em: https://app.uff.br/riuff/handle/1/1414. Acesso em: 16 abr. 2021.
Eaton, B. (1975). The equation for geopressure prediction from well logs. SPE Journal 5544. https://doi.org/10.2118/5544-MS
Gardner, G. H. F., Gardner, L. W., Gregory, A. R. (1974). Formation velocity and density – the diagnostics basics for stratigraphic traps. Geophysics, 39(6), 770-780. https://doi.org/10.1190/1.1440465
Haykin, S. (2001). Redes neurais princípios e prática. 2. ed. Porto Alegre: Bookman.
Hottmann, C. E., Johnson, R. K. (1965). Estimation of formation pressures from log-derived shale properties. Journal of Petroleum Technology, 17(6), 717-722. https://doi.org/10.2118/1110-PA
Laredo, J., Fontoura, S. A. B. (2007). Avanços na previsão de pressão de poros em folhelhos. 4º PDPETRO. Campinas. Disponível em: www.portalabpg.org.br/PDPetro/4/resumos/4PDPETRO_2_2_0324-1.pdf. Acesso em: 16 abr. 2021.
Oliveira, E. E., Fernandes, M. A., Ferreira, G. S. (2016). Uma reflexão sobre a importância da geomecânica para a Engenharia de Petróleo. II Congresso Nacional de Engenharia de Petróleo, Gás Natural e Biocombustíveis. Disponível em: https://editorarealize.com.br/artigo/visualizar/27080. Acesso em: 15 abr. 2021.
Ribeiro, G. S. (2006). Novas tecnologias em produção de petróleo. Rio de Janeiro: Petrobras. Disponível em: http://www.fem.unicamp.br/~instmed/Franca_SBPC_2006.pdf. Acesso em: 7 mar. 2018.
Rocha, L. A. S., Azevedo, C. T. (2009). Projetos de Poços de Petróleo: Geopressões e Assentamento de Colunas de Revestimento. 2ª ed. Rio de Janeiro: Interciência.
Santos, J. P. L., Andrade, J. F., Oliveira, R. C., Almeida Neto, J. B., Santos, A. P. P. (2015). Avaliação da aplicação dos métodos indiretos de predição do gradiente de pressão de poros em projetos de poços da Bacia Sergipe-Alagoas. Revista Eletrônica de Petróleo e Gás, 3, 31-40.
Scheid, C., Calçada, L. A., Meleiro, L. A. (2020). Desenvolvimento de novas tecnologias parra aplicação na perfuração de poços de petróleo.
Silva, I. N., Spatti, D. H., Flauzino, R. A. (2010). Redes neurais artificiais para Engenharia e Ciências Aplicadas (2 ed.). São Paulo: Artliber.
Silva, M. L. O., Leitão, S. R., Barros, N. S. (2015). Análise de redes neurais em variáveis de perfilagem, Sergipe. VII Simpósio de Engenharia de Produção de Sergipe. São Cristóvão: UFS. Disponível em: https://ri.ufs.br/jspui/handle/riufs/7800. Acesso em: 16 abr. 2021.
Souza, L. Z. (2011). Estudo do estado da arte da perfuração direcional de poços de petróleo. Trabalho de Conclusão de Curso. Vitória: Departamento de Engenharia Mecânica – UFES.
Teixeira, W., Toledo M. C. M., Fairchild T. R., Taioi F. (2000). Decifrando a Terra. São Paulo: Oficina de Textos.
Vasconcelos, R. R. (2014). Ajuste de parâmetros de correlações de densidade e tensão efetiva para estimativa do gradiente de pressão de poros. Trabalho de Conclusão de Curso. Niterói: Departamento de Engenharia Química e de Petróleo – UFF. Disponível em: https://app.uff.br/riuff/bitstream/1/2167/1/Raiza%20Vasconcelos.pdf. Acesso em: 16 abr. 2021.
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Copyright (c) 2021 Marianna Rezende de Morais Mendonça, Bruna Silveira Teixeira, Giovane Quadrelli, Ricardo Franciss
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