LAPSE:2023.11553
Published Article

LAPSE:2023.11553
Prediction of Temperature and Viscosity Profiles in Heavy-Oil Producer Wells Implementing a Downhole Induction Heater
February 27, 2023
Abstract
Very high viscosity significantly impacts the mobility of heavy crude oil representing difficulties in production and a decrease in the well’s efficiency. Downhole electric heating delivers a uniform injection of heat to the fluid and reservoir, resulting in a substantial decrease in dynamic viscosity due to its exponential relationship with temperature and a drop in frictional losses between the production zone and the pump intake. Therefore, this study predicts temperature and viscosity profiles in heavy oil-production wells implementing a downhole induction heater employing a simplified CFD model. For the development of the research, the geometry model was generated in CAD software based on the geometry provided by the BCPGroup and simulated in specialized CFD software. The model confirmed a 46.1% effective decrease of mean 12° API heavy-oil dynamic viscosity compared with simulation results without heating. The developed model was validated with experimental data provided by the BCPGroup, obtaining an excellent agreement with 0.8% and 15.69% mean error percentages for temperature and viscosity, respectively. Furthermore, CFD results confirmed that downhole electrical induction heating is an effective method for reducing heavy-oil dynamic viscosity; however, thermal effects in the reservoir due to heat penetration were insignificant. For this study, the well will remain stimulated.
Very high viscosity significantly impacts the mobility of heavy crude oil representing difficulties in production and a decrease in the well’s efficiency. Downhole electric heating delivers a uniform injection of heat to the fluid and reservoir, resulting in a substantial decrease in dynamic viscosity due to its exponential relationship with temperature and a drop in frictional losses between the production zone and the pump intake. Therefore, this study predicts temperature and viscosity profiles in heavy oil-production wells implementing a downhole induction heater employing a simplified CFD model. For the development of the research, the geometry model was generated in CAD software based on the geometry provided by the BCPGroup and simulated in specialized CFD software. The model confirmed a 46.1% effective decrease of mean 12° API heavy-oil dynamic viscosity compared with simulation results without heating. The developed model was validated with experimental data provided by the BCPGroup, obtaining an excellent agreement with 0.8% and 15.69% mean error percentages for temperature and viscosity, respectively. Furthermore, CFD results confirmed that downhole electrical induction heating is an effective method for reducing heavy-oil dynamic viscosity; however, thermal effects in the reservoir due to heat penetration were insignificant. For this study, the well will remain stimulated.
Record ID
Keywords
Computational Fluid Dynamics, downhole induction heater, enhanced oil recovery (EOR), heavy-oil producer wells, reservoir and well performance
Subject
Suggested Citation
Ramírez J, Zambrano A, Ratkovich N. Prediction of Temperature and Viscosity Profiles in Heavy-Oil Producer Wells Implementing a Downhole Induction Heater. (2023). LAPSE:2023.11553
Author Affiliations
Ramírez J: Department of Chemical and Food Engineering, Universidad de los Andes, Cra. 1 N °18A—12, Bogotá 111711, Colombia [ORCID]
Zambrano A: BCPGroup Artificial Lift, Autopista Medellín Km 0+440 Mts., Tenjo 250208, Colombia
Ratkovich N: Department of Chemical and Food Engineering, Universidad de los Andes, Cra. 1 N °18A—12, Bogotá 111711, Colombia [ORCID]
Zambrano A: BCPGroup Artificial Lift, Autopista Medellín Km 0+440 Mts., Tenjo 250208, Colombia
Ratkovich N: Department of Chemical and Food Engineering, Universidad de los Andes, Cra. 1 N °18A—12, Bogotá 111711, Colombia [ORCID]
Journal Name
Processes
Volume
11
Issue
2
First Page
631
Year
2023
Publication Date
2023-02-18
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11020631, Publication Type: Journal Article
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Published Article

LAPSE:2023.11553
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https://doi.org/10.3390/pr11020631
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Feb 27, 2023
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