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Filtros : "Journal of Petroleum Science and Engineering" "2019" Limpar

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  • Artigo de periodico

    Digital petrography: Mineralogy and porosity identification using machine learning algorithms in petrographic thin section images (2019)

    Rubo, Rafael Andrello; Carneiro, Cleyton de Carvalho ; Michelon, Mateus Fontana; Gioria, Rafael dos Santos

    Source: Journal of Petroleum Science and Engineering. Unidade: EP

    Subjects: INTELIGÊNCIA ARTIFICIAL, PETROGRAFIA, ROCHAS SEDIMENTARES

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      RUBO, Rafael Andrello et al. Digital petrography: Mineralogy and porosity identification using machine learning algorithms in petrographic thin section images. Journal of Petroleum Science and Engineering, v. 183, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.petrol.2019.106382. Acesso em: 08 nov. 2025.

    • APA

      Rubo, R. A., Carneiro, C. de C., Michelon, M. F., & Gioria, R. dos S. (2019). Digital petrography: Mineralogy and porosity identification using machine learning algorithms in petrographic thin section images. Journal of Petroleum Science and Engineering, 183. doi:10.1016/j.petrol.2019.106382

    • NLM

      Rubo RA, Carneiro C de C, Michelon MF, Gioria R dos S. Digital petrography: Mineralogy and porosity identification using machine learning algorithms in petrographic thin section images [Internet]. Journal of Petroleum Science and Engineering. 2019 ;183[citado 2025 nov. 08 ] Available from: https://doi.org/10.1016/j.petrol.2019.106382

    • Vancouver

      Rubo RA, Carneiro C de C, Michelon MF, Gioria R dos S. Digital petrography: Mineralogy and porosity identification using machine learning algorithms in petrographic thin section images [Internet]. Journal of Petroleum Science and Engineering. 2019 ;183[citado 2025 nov. 08 ] Available from: https://doi.org/10.1016/j.petrol.2019.106382

  • Artigo de periodico

    Influence of the Kalman gain localization in adaptive ensemble smoother history matching (2019)

    Ranazzi, Paulo Henrique; Pinto, Marcio Augusto Sampaio

    Source: Journal of Petroleum Science and Engineering. Unidade: EP

    Assunto: RESERVATÓRIOS DE PETRÓLEO

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      RANAZZI, Paulo Henrique e PINTO, Marcio Augusto Sampaio. Influence of the Kalman gain localization in adaptive ensemble smoother history matching. Journal of Petroleum Science and Engineering, v. 179, p. 244 - 256, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.petrol.2019.04.079. Acesso em: 08 nov. 2025.

    • APA

      Ranazzi, P. H., & Pinto, M. A. S. (2019). Influence of the Kalman gain localization in adaptive ensemble smoother history matching. Journal of Petroleum Science and Engineering, 179, 244 - 256. doi:10.1016/j.petrol.2019.04.079

    • NLM

      Ranazzi PH, Pinto MAS. Influence of the Kalman gain localization in adaptive ensemble smoother history matching [Internet]. Journal of Petroleum Science and Engineering. 2019 ; 179 244 - 256.[citado 2025 nov. 08 ] Available from: https://doi.org/10.1016/j.petrol.2019.04.079

    • Vancouver

      Ranazzi PH, Pinto MAS. Influence of the Kalman gain localization in adaptive ensemble smoother history matching [Internet]. Journal of Petroleum Science and Engineering. 2019 ; 179 244 - 256.[citado 2025 nov. 08 ] Available from: https://doi.org/10.1016/j.petrol.2019.04.079
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