Computational analysis of wax deposition in deep-water pipelines using nuclear techniques

Nalber Miranda Leite Nalber; Carlos Alberto Brayner de Oliveira Lira; Abel Gámez Rodriguez

doi:10.15392/2319-0612.2024.2760

Authors

Nalber Miranda Leite Nalber Northeast Regional Nuclear Science Center, 50.740-540, Recife, Pernambuco, Brazil. https://orcid.org/0000-0003-2344-941X
Carlos Alberto Brayner de Oliveira Lira Northeast Regional Nuclear Science Center, 50.740-540, Recife, Pernambuco, Brazil https://orcid.org/0000-0002-8287-4822
Abel Gámez Rodriguez Federal University of Pernambuco, 50.740-545, Recife, Pernambuco, Brazil https://orcid.org/0000-0002-1584-6768

DOI:

https://doi.org/10.15392/2319-0612.2024.2760

Keywords:

wax deposition, nuclear technique, gamma radiation, Monte Carlo method

Abstract

Wax deposition in oil pipelines is a problem that affects flow assurance because it restricts production and, in more extreme cases, causes pipeline blockages. This problem occurs more frequently in offshore environments, where most of Brazil's reservoirs are located and where the ocean temperature at great depths is around 5°C. Detecting the wax layer on the inside walls of pipelines at an early stage avoids unscheduled stoppages and major economic losses. Among the various methods and techniques found in the literature for monitoring wax deposition, nuclear techniques are distinguished by the fact that their use does not interfere with the physical integrity of the pipeline, by the non-intrusive and indirect (non-contact) mode of operation and, therefore, does not affect the oil transportation process. This paper presents a computational model using the Monte Carlo N-Particle 6 (MCNP6) code and the gamma radiation transmission profiling technique to detect the presence of wax on the inner walls of pipelines used for deepwater oil transportation. The results of this study show that the model can detect the presence of up to 5% wax (in relation to the internal radius of the pipeline) with an accuracy of 7.4% in pipelines used in deep waters.

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References

[1] MATOS, S. F.; ALTOÉ, L. Analysis of deepwater oil flow assurance in relation to wax deposition. Latin American Journal of Energy Research, vol. 6, no 2, p. 12–31, 2020, doi: 10.21712/lajer.2019.v6.n2.p12-31. DOI: https://doi.org/10.21712/lajer.2019.v6.n2.p12-31

[2] PORTO, T. R. N.; LIMA, A. G. B. De. Transient flow of waxy oil in a circular section pipeline: modeling and simulation, Holos, vol. 1, p. 155–173, 2017, doi: 10.15628/holos.2017.5220. DOI: https://doi.org/10.15628/holos.2017.5220

[3] AL-YAARI, M. wax deposition: mitigation and removal techniques. Society of Petroleum Engineers, p. 14–16, 2011. DOI: https://doi.org/10.2118/155412-MS

[4] THEYAB, M. A. Wax deposition process: mechanisms, affecting factors and mitigation methods. Open Access Journal of Science, vol. 2, no 2, mar. 2018, doi: 10.15406/oajs.2018.02.00054. DOI: https://doi.org/10.15406/oajs.2018.02.00054

[5] MATZAIN, A.; APTE, M. S.; ZHANG, H. Q.; VOLK, M.; BRILL, J. P.; CREEK, J. L. Investigation of paraffin deposition during multiphase flow in pipelines and wellbores - Part 1: Experiments. Journal of Energy Resources Technology, Transactions of the ASME, vol. 124, no 3, p. 180–186, set. 2002, doi: 10.1115/1.1484392. DOI: https://doi.org/10.1115/1.1484392

[6] BORDALO, S. N.; OLIVEIRA, R. Biphasic oil-water flow with wax precipitation in subsea oil production pipelines, 4° Congresso Brasileiro de Petróleo e Gás - PDPETRO, Campinas, São Paulo: Associação Brasileira de Pesquisa e Desenvolvimento em Petróleo e Gás - ABPG , out. 2007, p. 12.

[7] CHEN, X. T.; BUTLER, M.; VOLK, M. Techniques for measuring wax thickness during single and multiphase flow, SPE Annual Technical Conference and Exhibition, San Antonio, Texas: Society of Petroleum Engineers, out. 1997, p. 1–8. DOI: https://doi.org/10.2118/38773-MS

[8] VIANA, C. PIG Passage - Critical Operation: Concepts, Operations and Recommendations, LinkedIn. Accessed: May 30, 2023. [Online]. Available at: https://www.linkedin.com/pulse/passagem-de-pig-operação-crítica-conceitos-operações-viana/?originalSubdomain=pt

[9] MORAIS, J. M. Deepwater Oil: A Technological History of PETROBRAS in Offshore Exploration and Production. Brasília: PETROBRAS, 2013.

[10] MAJID, S. A.; MELAIBARI, A; MALKI, B. Hydrocarbon scale deposits measurements by neutron moderation and capture gamma methods, Nuclear Instruments and Methods in Physics Research B, vol. 119, p. 433–437, 1996. DOI: https://doi.org/10.1016/0168-583X(96)00296-0

[11] HOFFMANN, R.; AMUNDSEN, L.; SCHÜLLER, R. Online monitoring of wax deposition in sub-sea pipelines, Meas Sci Technol, vol. 22, no 7, 2011, doi: 10.1088/0957-0233/22/7/075701. DOI: https://doi.org/10.1088/0957-0233/22/7/075701

[12] CHEN et al., H. Ultrasonic detection and analysis of wax appearance temperature of kingfisher live oil, Energy and Fuels, vol. 28, no 4, p. 2422–2428, abr. 2014, doi: 10.1021/ef500036u. DOI: https://doi.org/10.1021/ef500036u

[13] MEI, I. L. S.; ISMAIL, I.; SHAFQUET, A.; ABDULLAH, B. Real-time monitoring and measurement of wax deposition in pipelines via non-invasive electrical capacitance tomography, Meas Sci Technol, vol. 27, no 2, dez. 2015, doi: 10.1088/0957-0233/27/2/025403. DOI: https://doi.org/10.1088/0957-0233/27/2/025403

[14] SOARES, L. L. O. Determination of the onset of paraffin deposition in oil production and transportation pipelines using a Multipoint Temperature Sensor. Federal University of Bahia, Polytechnic School, Salvador, 2017.

[15] OLIVEIRA, A. A. Historical success stories in the use of MAD-pig to locate obstructions in pipelines, Technical Bulletin of Oil Production, vol. 1, no 1, Rio de Janeiro, p. 95–126, 2006.

[16] KOPTEVA, A.; KOPTEV, V.; MALAREV, V.; USHKOVA, T. Development of a system for automated control of oil transportation in the Arctic region to prevent the formation of wax deposits in pipelines, Proceedings of EECE 2019: Energy, Environmental and Construction Engineering, St. Petersburg, Russia: EDP Sciences, nov. 2019. doi: 10.1051/e3sconf/201914007004. DOI: https://doi.org/10.1051/e3sconf/201914007004

[17] LOPES, R. T.; VALENTE, C. M.; DE JESUS, E. F. O.; CAMERINI, C. S. Detection of paraffin deposition inside a draining tubulation by the Compton Scattering Technique, Applied Radiation and Isotopes, vol. 48, no 10–12, p. 1443–1450, 1997, doi: 10.1016/S0969-8043(97)00255-8. DOI: https://doi.org/10.1016/S0969-8043(97)00255-8

[18] KOPTEVA, A.; STARSHAYA, V. Radioisotope measuring system for oil stream asphaltene-resin-paraffin deposits ARPD parameters. SPE Russian Petroleum Technology Conference and Exhibition, Moscow, Russia: Society of Petroleum Engineers, out. 2016, p. 1–7. DOI: https://doi.org/10.2118/182104-RU

[19] ABDUL-MAJID, S. Determination of wax deposition and corrosion in pipelines by neutron back diffusion collimation and neutron capture gamma rays, Applied Radiation and Isotopes, vol. 74, p. 102–108, abr. 2013, doi: 10.1016/j.apradiso.2013.01.012. DOI: https://doi.org/10.1016/j.apradiso.2013.01.012

[20] TAUHATA, L.; SALATI, I.; PRINZIO, R. D.; PRINZIO, A. R. D. Radioprotection and Dosimetry: Fundamentals, 10o ed. Rio de Janeiro: Comissão Nacional de Energia Nuclear, 2014.

[21] JOHANSEN, G. A.; JACKSON, P. Radioisotope Gauges for Industrial Process Measurements. Southern Gate, Chichester: John Wiley & Sons, 2004. DOI: https://doi.org/10.1002/0470021098

[22] KNOLL, G. F. Radiation Detection and Measurement, 4o ed. Ann Arbor, Michigan: John Wiley & Sons, 2010.

[23] LEITE, N. M.; LIRA, C. A. B. O.; RODRIGUEZ, A. G. Computational analysis for wax detection in deepwater pipelines using nuclear techniques. Brazilian Journal of Radiation Sciences, vol. 11, no 1A (Suppl.), p. 1–20, jul. 2023, doi: 10.15392/2319-0612.2023.2193. DOI: https://doi.org/10.15392/2319-0612.2023.2193

[24] BESERRA, M. T. F. Assessment of scale thickness in oil extraction pipelines. Institute of Radiation Protection and Dosimetry, Rio de Janeiro, 2012.

[25] SOARES, M. Fouling Detection System in Oil Pipelines Using Gamma Transmission Technique. Federal University of Rio de Janeiro, Rio de Janeiro, 2014.

[26] YORIYAZ, H. Monte Carlo Method: principles and applications in Medical Physics. Brazilian Journal of Medical Physics, vol. 3, no 1, p. 141–149, 2009.

[27] GOORLEY, J. T.; JAMES, M. R.; BOOTH, T. E.; BROWN, F. B.; BULL, J. S.; COX, L. J.; DURKEE, J. W. J.; ELSON, J. S.; FENSIN, MICHAEL LORNE FORSTER, ROBERT A. III HENDRICKS, J. S.; HUGHES, H. G. I.; JOHNS, R. C.; KI, A. J. Initial MCNP6 release overview -MCNP6 version 1.0. Los Alamos: Los Alamos National Laboratory, 2013. DOI: https://doi.org/10.2172/1086758

[28] LOS ALAMOS NATIONAL LABORATORY. Monte Carlo N–Particle Transport Code System Including MCNP6.1, MCNP5-1.60, MCNPX-2.7.0 and Data Libraries. Los Alamos, New Mexico: Radiation Safety Information Computational Center, 2013.

[29] JOHANSEN, G. A.; JACKSON, P. Salinity independent measurement of gas volume fraction in oil/gas/water pipe flows, Applied Radiation and Isotopes, vol. 53, p. 595–601, 2000, [Online]. Disponível em: www.elsevier.com/locate/apradiso DOI: https://doi.org/10.1016/S0969-8043(00)00232-3

[30] SALGADO, C. M. Identification of Flow Regimes and Prediction of Volume Fractions in Multiphase Systems Using Nuclear Technique and Artificial Neural Network. Federal University of Rio de Janeiro, Rio de Janeiro, 2010.

[31] YEH, M. K.; KYRIAKIDES, V. Collapse of Deepwater Pipelines. 18th Offshore Technology Conference, Houston, Texas: American Society of Mechanical Engineers, maio 1986. DOI: https://doi.org/10.4043/5215-MS

[32] GOUVEIA, J. C. C. Critical engineering analysis for rigid pipes submitted to large deformations. Rio de Janeiro: Fluminense Federal University, 2010.

[33] TUBOS ABC, API 5L tubes grades X42 to X80. ABC Tubes. Acessado: 20 de maio de 2022. [Online]. Disponível em: https://www.tubosabc.com.br/tubos/tubos-api-5l/?doing_wp_cron=1684622473.7044830322265625000000

[34] TYCOON PIPING SOLUTION. API 5L X65 PSL2 Pipe. Acessado: 13 de julho de 2023. [Online]. Disponível em: https://www.oilandgaspipingmaterials.com/iso-3183-l450-api5l-x65-psl1-psl2-pipe-suppliers.html

[35] MCCONN, R.; GESH, C.; PAGH, R.; RUCKER; WILLIAMS, R. Compendium of material composition data for radiation transport modeling. Washington: Pacific Northwest National Laboratory, 2011. DOI: https://doi.org/10.2172/1023125

[36] NATIONAL AGENCY OF PETROLEUM, NATURAL GAS AND BIOFUELS, Oil and Natural Gas Production Bulletin No. 152. Acessado: 25 de junho de 2023. [Online]. Disponível em: https://www.gov.br/anp/pt-br/centrais-de-conteudo/publicacoes/boletins-anp/boletins/arquivos-bmppgn/2023/boletim-abril.pdf

[37] NATIONAL AGENCY OF PETROLEUM, NATURAL GAS AND BIOFUELS, Oil and Natural Gas Production Bulletin No. 121. Acessado: 1o de fevereiro de 2023. [Online]. Disponível em: https://www.gov.br/anp/pt-br/centrais-de-conteudo/publicacoes/boletins-anp/boletins/arquivos-bmppgn/2020/boletim-12-2020.pdf

[38] MALAREV, V. I.; KOPTEVA, A. V. Using radioisotope method for measuring ice layer thickness in pulp lines. IOP Conf Ser Earth Environ Sci, vol. 87, no 3, 2017, doi: 10.1088/1755-1315/87/3/032022. DOI: https://doi.org/10.1088/1755-1315/87/3/032022

[39] DOBBS, J. B. A unique method of wax control in production operations. SPE Rocky Mountain Regional Meeting, Gillette, Wyoming: Society of Petroleum Engineers Inc, maio 1999, p. 1–6. DOI: https://doi.org/10.2118/55647-MS

[40] FERREIRA, C. A. M. Detection of annular flooding in flexible ducts using the gamma radiation transmission technique. Federal University of Rio de Janeiro, Rio de Janeiro, 2021.

[41] GUEDES, K. A. N. Simulation using the MCNPX code for gamma tomography and validation with experimental data. Federal University of Pernambuco, Recife, 2016.

[42] MCCAW, D. D.; HULBERT, V. G.; SMITH, A. E. Gamma scanning of large sieve tray towers”. NUCLEX 75: International Nuclear Industries Fair and Technical Meeetings, Basel, Switzerland: Atomic Energy of Canada Limited, out. 1975, p. 1–13.

[43] CARNEIRO JUNIOR, C. Development of a Gamma Transmission-Based Inspection System for Application in Flexible Pipes and Industrial Columns. Federal University of Rio de Janeiro, Rio de Janeiro, 2005.

[44] TEIXEIRA, T. P. Prediction of scale thickness in pipelines used in oil transportation using gamma radiation and artificial neural network. Institute of Nuclear Engineering, Rio de Janeiro, 2018.

[45] OLIVEIRA, D. F.; NASCIMENTO, J. R.; MARINHO, C. A.; LOPES, R. T. Gamma transmission system for detection of scale in oil exploration pipelines. Nuclear Instruments and Methods in Physics Research A, vol. 784, p. 616–620, jun. 2015, doi: 10.1016/j.nima.2014.11.030. DOI: https://doi.org/10.1016/j.nima.2014.11.030