• DocumentCode
    402905
  • Title

    Investigation on the applicability of oil/water two-phase profiles interpretation based on temperature and flowmeter logs

  • Author

    Jin, Ning-de ; Nie, Xiang-bin ; Yin, Zhong ; Zhao, Feng-hua

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Tianjin Univ., China
  • Volume
    1
  • fYear
    2003
  • fDate
    2-5 Nov. 2003
  • Firstpage
    390
  • Abstract
    Temperature and flowmeter logs are two must ones in the production logging combination tool, but the temperature logs are always being only qualitatively analyzed and the abundant borehole information they hold are in great need to be mined. Started from the thermal transfer and mass transfer phenomena of the two-phase flow in the "formation-borehole" system of the production wells, based on the mass and energy conservation equations, a recursive arithmetic to interpret oil/water two-phase profiles with temperature and fluids flux information has been proposed. A comprehensive study of the effects of each parameter on the profiles interpretation has been carried out, and the potential error trend estimations of the interpretation in oil and water flow flux have been concluded. It has been shown that this method, without any new logging techniques, makes the most of the abundant temperature logs in the field and mines the quantitative information of them, which makes the best of the existing resource and has good applicability and practical values.
  • Keywords
    data recording; flowmeters; oil technology; energy conservation equation; flowmeter logs; fluids flux information; formation-borehole system; mass conservation equation; mass transfer phenomena; oil/water two-phase profiles interpretation; production logging combination tool; temperature logs; thermal transfer; water flow flux; Arithmetic; Energy conservation; Equations; Flow production systems; Information analysis; Mass production; Petroleum; Temperature; Water conservation; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2003 International Conference on
  • Print_ISBN
    0-7803-8131-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2003.1264508
  • Filename
    1264508