Fluid level prediction for separator in oilfield using scattering gamma ray and artificial neural network

Autores

  • César Marques Salgado Instituto de Engenharia Nuclear
  • Rogério Chaffin Nunes Instituto de Engenharia Nuclear

Palavras-chave:

MCNP-X code, fluid level, scattering gamma ray, artificial neural network

Resumo

In this study, the recorded backscatter gamma ray pulse height distributions from a detector together with Artificial Neural Network (ANN) has sufficient information to calculate the fluid level in multiphase flows. A multilayer perceptron ANN is used for predict the fluid level from data recorded by detector.

Biografia do Autor

César Marques Salgado, Instituto de Engenharia Nuclear

DIRA

Rogério Chaffin Nunes, Instituto de Engenharia Nuclear

SEREA

Referências

SALGADO, C. M et al. Prediction of volume fractions in three-phase flows using nuclear technique and artificial neural network. Applied Radiation and Isotopes, Amsterdam, v. 67, n. 10, p. 1812-1818, 2009.

SALGADO, W. L.; BRANDÃO, L. E. B. B. Study of volume fractions on biphasic stratified regime using gamma ray. In: INTERNATIONAL NUCLEAR ATLANTIC CONFERENCE, - ENAN - Meeting on Nuclear Applications, 13., 2017, Belo Horizonte. Anais… Rio de Janeiro: ABEN, 2017. Não paginado.

Capa Progress Report 2015-2017

Downloads

Publicado

2021-07-08

Como Citar

Salgado, C. M., & Nunes, R. C. (2021). Fluid level prediction for separator in oilfield using scattering gamma ray and artificial neural network. Instituto De Engenharia Nuclear: Progress Report, (3), 21. Recuperado de https://revistas.ien.gov.br/index.php/ienprogressreport/article/view/324

Edição

n. 3 (2018): IEN - Progress Report 2015-2017 n.3

Seção

Application of Nuclear Techniques in Health and Environment

Licença

Copyright (c) 2018 César Marques Salgado, Rogério Chaffin Nunes

Creative Commons License

Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.