Mathematical Modelling and Applications

| Peer-Reviewed |

An Improved Model for Predicting Fluid Temperature in Deep Wells

Received: 17 July 2016    Accepted: 14 October 2016    Published: 21 October 2016
Views:       Downloads:

Share This Article

Abstract

The objective of this study was to develop an improved method to predict fluid temperature profiles in high-temperature wells for designing production string in deep-water development. The method was developed on the basis of heat transfer involves heat convection and conduction inside the production string and in the annular space. The governing equations were solved using the method of characteristics, resulting in two simple closed-form equations. The method was coded in a spreadsheet for easy applications. Data from three wells were employed to check the accuracy of the new method. Comparisons of results from Hasan's method, Gilbertson et al.'s method, and the new method with temperature data measured in two gas-lift wells show that the new method best predicts well temperatures in trend. A comparison of results given by Mao's method and the new method with temperatures observed in a deep-water gas well testing indicates that the new method better predicts well temperatures with errors less than 4%. This work provides petroleum engineers a simple and accurate method for predicting temperature profiles in oil and gas production operations, especially deep-water operations. It eliminates the need for sophisticated analytical and numerical models in fluid temperature analysis.

DOI 10.11648/j.mma.20160101.14
Published in Mathematical Modelling and Applications (Volume 1, Issue 1, October 2016)
Page(s) 20-25
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Fluid Temperature, Deep Wells, Gas-Lift Wells, Heat Transfer

References
[1] Sagar, R., Doty, D. R., and Schmidt, Z. 1991. Predicting Temperature Profiles in a Flowing Well. SPE Production Engineering 6 (04): 441-448. SPE-19702-PA. doi: 10.2118/19702-PA.
[2] Ramey, H. J. 1962. Wellbore Heat Transmission. Journal of Petroleum Technology 14 (04): 427-435. SPE-96-PA. doi: 10.2118/96-PA.
[3] Alves, I. N., Alhanati, F. J. S., & Shoham, O. 1992. A Unified Model for Predicting Flowing Temperature Distribution in Wellbores and Pipelines. Presented at SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, USA, 23-26 September. SPE- 152039-MS. doi: 10.2118/20632-PA.
[4] Hasan, A. R., and Kabir, C. S. 1994. Aspects of Wellbore Heat Transfer During Two-Phase Flow (includes associated papers 30226 and 30970). SPE Production & Facilities 9 (03): 211-216. SPE-22948-PA. doi: 10.2118/22948-PA.
[5] King, V. P. S., Coelho, L. C., Guigon, J., Cunha, G., and Landau, L. 2005. Analytical Solution for Transient Temperature Field Around a Cased and Cemented Wellbore. Presented at SPE Latin American and Caribbean Petroleum Engineering Conference, Rio de Janeiro, Brazil, 20-23 June. SPE- 94870-MS. doi: 10.2118/94870-MS.
[6] Guo, B., Duan, S., and Ghalambor, A. 2006. A Simple Model for Predicting Heat Loss and Temperature Profiles in Insulated Pipelines. SPE Production & Operations 21 (01): 107-113. doi: 10.2118/86983-PA.
[7] Spindler, R. P. 2011. Analytical Models for Wellbore-Temperature Distribution. SPE Journal 16 (01): 125-133. SPE-140135-PA. doi: 10.2118/140135-PA
[8] Satter, A. 1965. Heat Losses during Flow of Steam down a Wellbore. Journal of Petroleum Technology 17 (07): 845-851. SPE-1071-PA. doi: 10.2118/1071-PA.
[9] Huygen, H. H. A., & Huitt, J. L. 1966. Wellbore Heat Losses and Casing Temperatures during Steam Injection. Presented at Drilling and Production Practice, New York, New York, USA, 1 January. API-66-025.
[10] Back, L. H., and Cuffel, R. F. 1978. Analysis of Heat Losses and Casing Temperatures of Steam Injection Wells with Annular Coolant Water Flow. Presented at SPE California Regional Meeting, San Francisco, California, USA, 12-14 April. SPE- 7148-MS. doi: 10.2118/7148-MS.
[11] Durrant, A. J., and Thambynayagam, R. K. M. 1986. Wellbore Heat Transmission and Pressure Drop for Steam/Water Injection and Geothermal Production: A Simple Solution Technique. SPE Reservoir Engineering 1 (02): 148-162. SPE-12939-PA. doi: 10.2118/12939-PA.
[12] Pacheco, E. F., & Ali, S. M. F. 1972. Wellbore Heat Losses and Pressure Drop In Steam Injection. Journal of Petroleum Technology 24 (02): 139-144. SPE-3428-PA. doi: 10.2118/3428-PA.
[13] Chiu, K., and Thakur, S. C. 1991. Modeling of Wellbore Heat Losses in Directional Wells under Changing Injection Conditions. Presented at SPE Annual Technical Conference and Exhibition, Dallas, Texas, USA, 6-9 October. SPE- 22870-MS. doi: 10.2118/22870-MS.
[14] Kirkpatrick, C. V. 1959. Advances in Gas-lift Technology. Presented at Drilling and Production Practice, New York, New York, USA, 1 January. API-59-024.
[15] Winkler, H. W., and Eads, P. T. 1989. Algorithm for More Accurately Predicting Nitrogen-Charged Gas-Lift Valve Operation at High Pressures and Temperatures. Presented at SPE Production Operations Symposium, Oklahoma City, Oklahoma, USA, 13-14 March. SPE- 18871-MS. doi: 10.2118/18871-MS.
[16] Lagerlef, D. L., Smalstig, W. H., and Erwin, M. D. 1992. Gas-Lift-Valve Test Rack Opening Design Methodology for Extreme Kickoff Temperature Conditions. Presented at SPE Western Regional Meeting, Bakersfield, California, USA, 30 March-1 April. SPE- 24065-MS. doi: 10.2118/24065-MS.
[17] Hasan, A. R., and Kabir, C. S. 1996. A Mechanistic Model for Computing Fluid Temperature Profiles in Gas-Lift Wells. SPE Production & Facilities 11 (03): 179-185. SPE-26098-PA. doi: 10.2118/26098-PA.
[18] Hernandez, A., Garcia, G., Concho, A. M., Garcia, R., and Navarro, U. 1998. Downhole Pressure and Temperature Survey Analysis for Wells on Intermittent Gas Lift. Society of Petroleum Engineers. doi: 10.2118/39853-MS.
[19] Yu, Y., Lin, T., Xie, H., Guan, Y., and Li, K. 2009. Prediction of Wellbore Temperature Profiles During Heavy Oil Production Assisted With Light Oil Lift. Presented at SPE Production and Operations Symposium, Oklahoma, USA, 4-8 April. SPE- 119526-MS. doi: 10.2118/119526-MS.
[20] Gilbertson, E., Hover, F., and Freeman, B. 2013. A Thermally Actuated Gas-Lift Safety Valve. SPE Production & Operations 28 (01): 77-84. SPE-161930-PA. doi: 10.2118/161930-PA.
[21] Han, G., Ling, K., and Zhang, Z. 2014. A Transient Two-Phase Fluid- and Heat-Flow Model for Gas-Lift-Assisted Waxy-Crude Wells with Periodical Electric Heating. Presented at SPE Heavy Oil Conference-Canada, Calgary, Alberta, Canada, 11-13 June. SPE-165415-MS. doi: 10.2118/165415-MS.
[22] Wooley, G. R. 1980. Computing Downhole Temperatures in Circulation, Injection, and Production Wells. Journal of Petroleum Technology 32 (09): 1509 – 1522. SPE-8441-PA. doi: 10.2118/8441-PA.
[23] Leutwyler, K. 1966. Casing Temperature Studies in Steam Injection Wells. Journal of Petroleum Technology 18 (09): 1,157 - 1,162. SPE- 1264-PA. doi: 10.2118/1264-PA.
[24] Tragesser, A. F., Crawford, P. B., & Crawford, H. R. 1967. A Method for Calculating Circulating Temperatures. Journal of Petroleum Technology 19 (11): 1,507-1,512. SPE-1484-PA. doi: 10.2118/1484-PA.
[25] Nelson, W. C. 1977. Circulating Temperatures Existing Prior To Cementing Casing In Prudhoe Bay Wells. Presented at SPE Annual Fall Technical Conference and Exhibition, Denver, Colorado, USA, 9-12 October. SPE- 6802-MS. doi: 10.2118/6802-MS.
[26] Mao, J. and Liu, Q. (2016). Temperature prediction model of gas wells for deep-water testing in South China Sea. Personal communication, JNGSE-D-16-0101.
Author Information
  • Petroleum Engineering Department, University of Louisiana at Lafayette, Louisiana, USA

  • Petroleum Engineering Department, University of Louisiana at Lafayette, Louisiana, USA

Cite This Article
  • APA Style

    Boyun Guo, Jinze Song. (2016). An Improved Model for Predicting Fluid Temperature in Deep Wells. Mathematical Modelling and Applications, 1(1), 20-25. https://doi.org/10.11648/j.mma.20160101.14

    Copy | Download

    ACS Style

    Boyun Guo; Jinze Song. An Improved Model for Predicting Fluid Temperature in Deep Wells. Math. Model. Appl. 2016, 1(1), 20-25. doi: 10.11648/j.mma.20160101.14

    Copy | Download

    AMA Style

    Boyun Guo, Jinze Song. An Improved Model for Predicting Fluid Temperature in Deep Wells. Math Model Appl. 2016;1(1):20-25. doi: 10.11648/j.mma.20160101.14

    Copy | Download

  • @article{10.11648/j.mma.20160101.14,
      author = {Boyun Guo and Jinze Song},
      title = {An Improved Model for Predicting Fluid Temperature in Deep Wells},
      journal = {Mathematical Modelling and Applications},
      volume = {1},
      number = {1},
      pages = {20-25},
      doi = {10.11648/j.mma.20160101.14},
      url = {https://doi.org/10.11648/j.mma.20160101.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.mma.20160101.14},
      abstract = {The objective of this study was to develop an improved method to predict fluid temperature profiles in high-temperature wells for designing production string in deep-water development. The method was developed on the basis of heat transfer involves heat convection and conduction inside the production string and in the annular space. The governing equations were solved using the method of characteristics, resulting in two simple closed-form equations. The method was coded in a spreadsheet for easy applications. Data from three wells were employed to check the accuracy of the new method. Comparisons of results from Hasan's method, Gilbertson et al.'s method, and the new method with temperature data measured in two gas-lift wells show that the new method best predicts well temperatures in trend. A comparison of results given by Mao's method and the new method with temperatures observed in a deep-water gas well testing indicates that the new method better predicts well temperatures with errors less than 4%. This work provides petroleum engineers a simple and accurate method for predicting temperature profiles in oil and gas production operations, especially deep-water operations. It eliminates the need for sophisticated analytical and numerical models in fluid temperature analysis.},
     year = {2016}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - An Improved Model for Predicting Fluid Temperature in Deep Wells
    AU  - Boyun Guo
    AU  - Jinze Song
    Y1  - 2016/10/21
    PY  - 2016
    N1  - https://doi.org/10.11648/j.mma.20160101.14
    DO  - 10.11648/j.mma.20160101.14
    T2  - Mathematical Modelling and Applications
    JF  - Mathematical Modelling and Applications
    JO  - Mathematical Modelling and Applications
    SP  - 20
    EP  - 25
    PB  - Science Publishing Group
    SN  - 2575-1794
    UR  - https://doi.org/10.11648/j.mma.20160101.14
    AB  - The objective of this study was to develop an improved method to predict fluid temperature profiles in high-temperature wells for designing production string in deep-water development. The method was developed on the basis of heat transfer involves heat convection and conduction inside the production string and in the annular space. The governing equations were solved using the method of characteristics, resulting in two simple closed-form equations. The method was coded in a spreadsheet for easy applications. Data from three wells were employed to check the accuracy of the new method. Comparisons of results from Hasan's method, Gilbertson et al.'s method, and the new method with temperature data measured in two gas-lift wells show that the new method best predicts well temperatures in trend. A comparison of results given by Mao's method and the new method with temperatures observed in a deep-water gas well testing indicates that the new method better predicts well temperatures with errors less than 4%. This work provides petroleum engineers a simple and accurate method for predicting temperature profiles in oil and gas production operations, especially deep-water operations. It eliminates the need for sophisticated analytical and numerical models in fluid temperature analysis.
    VL  - 1
    IS  - 1
    ER  - 

    Copy | Download

  • Sections