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

Authors

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

Keywords:

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

Abstract

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.

Author Biographies

César Marques Salgado, Instituto de Engenharia Nuclear

DIRA

Rogério Chaffin Nunes, Instituto de Engenharia Nuclear

SEREA

References

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

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Published

2021-07-08

How to Cite

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. Retrieved from https://revistas.ien.gov.br/index.php/ienprogressreport/article/view/324

Issue

No. 3 (2018): IEN - Progress Report 2015-2017 n.3

Section

Application of Nuclear Techniques in Health and Environment

License

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

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.