Study on the Influence Law of Temperature Profile of Water Injection Well
Abstract - 268
PDF

Keywords

DTS
Orthogonal test
Water injection well
Temperature profile prediction model
The influence law of temperature profile

How to Cite

1.
Hanbin Z, Wenqiang L, Hongwen L, Haitao L, Hansong M, Ying L, Beibei J, Yuxing X, Qin Z. Study on the Influence Law of Temperature Profile of Water Injection Well. Int. J. Petrol. Technol. [Internet]. 2023 May 10 [cited 2024 Jul. 17];10:1-13. Available from: https://avantipublishers.com/index.php/ijpt/article/view/1369

Funding data

Abstract

Due to the lack of knowledge on the influence law of the temperature profile of layered water injection wells, it is still highly challenging to quantitatively diagnose the water injection profile of layered water injection wells using distributed optical fiber temperature sensing (DTS). In this paper, a temperature profile prediction model for layered water injection wells has been developed by considering the micro-thermal effect and non-isothermal reservoir seepage. The influence of various single-factor changes on the temperature profile of layered water injection wells is simulated and analyzed. Orthogonal experiment analysis results demonstrate that the sensitivity of different factors on wellbore temperature from strong to weak is the injection temperature of the water, injection time, water injection rate, wellbore diameter, formation thermal conductivity, wellbore trajectory, and the permeability of injection formations (Tinj>t>Qinj>D>Kt>θ>k). The injection temperature of water, injection time, and water injection rate are the dominant factors affecting the temperature profile of water injection wells. The results of this paper provide a theoretical foundation for the accurate evaluation of the water injection profile and water injection scheme optimization for the layered water injection wells.

https://doi.org/10.15377/2409-787X.2023.10.1
PDF

References

Liu H, Pei X, Luo K, Sun F, Zheng L, Yang Q. Status quo and development trend of layered water injection technology for oil and gas field development in China. Pet Explor Dev 2013; 40: 785-90.

Sui YY, Li ZP, Wang JQ, Ye YZ, Li YL. Prediction of water injection profile using implicit nonlinear method. Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Natural Science). 2010; 34: 95-8. https://doi.org/10.3969/j.issn.1673-5005.2010.06.018

Li Xiaorong, Liu X, Zhang Y, Fang G, Xindong W, Yongcun F. Application and progress of oil and gas well engineering monitoring technology based on distributed optical fiber acoustic sensor. Pet Drill Prod Proc. 2022; 44: 309-20.

Kurashima T, Horiguchi T, Tateda M. Distributed-temperature sensing using stimulated Brillouin scattering in optical silica fibers. Opt Lett. 1990; 15: 1038-40. https://doi.org/10.1364/OL.15.001038

Culverhouse D, Farahi F, Pannell CN, Jackson DA. Potential of stimulated Brillouin scattering as sensing mechanism for distributed temperature sensors. Electron Lett. 1989; 25: 913-5. https://doi.org/10.1049/el:19890612

Luo H, Li H, Jiang B. A new interpretation method for production profile of fractured horizontal wells in low permeability gas reservoirs based on DTS data inversion. Nat Gas Geosci. 2019; 30: 1639-45.

Luo H, Li H, An S. Analysis on influencing factors of temperature profile of fractured horizontal well in tight gas reservoir. Special Oil and Gas Reservoirs. 2021; 28: 150-7.

Wheaton B, Haustveit K, Deeg W, Miskimins J, Barree R. A case study of completion effectiveness in the eagle ford shale using DAS/DTS observations and hydraulic fracture modeling, SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, USA: SPE; 9-11 February 2016. https://doi.org/10.2118/179149-ms

Achnivu OI, Zhu D, Furui K. Interpretation method of downhole temperature and pressure data for detecting water entry in inclined gas wells. SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA: SPE; 21-24 September 2008. https://doi.org/10.2118/115753-MS

Molenaar MM, Fidan E, Hill DJ. Real-time downhole monitoring of hydraulic fracturing treatments using Fibre Optic Distributed Temperature and acoustic sensing. SPE/EAGE European Unconventional Resources Conference and Exhibition, Vienna, Austria: SPE; 20-22 March 2012. https://doi.org/10.2118/152981-MS

Ugueto GA, Huckabee PT, Molenaar MM. Challenging assumptions about fracture stimulation placement effectiveness using fiber optic distributed sensing diagnostics: diversion, stage isolation and overflushing. SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, USA: SPE; 3-5 February 2015. https://doi.org/10.2118/SPE-173348-MS

Zhang S, Zhu D. Inversion of downhole temperature measurements in multistage fracture stimulation in horizontal wells. SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA: SPE; 9-11 October 2017. https://doi.org/10.2118/187322-MS

Li H, Luo H, Xiang Y, Li Y, Jiang B, Cui X, et al. DTS based artificial fracture identification and production profile interpretation method for shale gas horizontal wells. Natural Gas Industry. 2021; 8: 494-504. https://doi.org/10.1016/j.ngib.2021.05.001

Hansong M, Luo H, Haitao L, Yuxing X, Qin Z, Ying L. Study on the influence law of temperature profile of vertical wells in gas reservoirs. Int J Pet Technol. 2022; 9: 54-66. https://doi.org/10.15377/2409-787X.2022.09.7

Ramey HJ. Wellbore heat transmission. J Pet Technol. 1962; 14: 427-35. https://doi.org/10.2118/96-PA

Feng E, Yan G, Hu Z. Numerical simulation and optimization of temperature field in formation zone of water injection well. J Pet. 1996: 96-102.

Gao P. Numerical calculation of well temperature logging. Jilin University; 2007.

Xiao Z. Numerical simulation of downhole temperature field of water injection well. Daqing Petroleum Institute; 2002.

Sagar R, Doty DR, Schmldt Z. Predicting temperature profiles in a flowing well. SPE Prod Eng. 1991; 6: 441-8. https://doi.org/10.2118/19702-PA

Yoshioka K, Zhu D, Hill AD, Dawkrajai P, Lake LW. Prediction of temperature changes caused by water or gas entry into a horizontal well. SPE Prod Oper. 2007; 22: 425-33. https://doi.org/10.2118/100209-PA

Yoshioka K, Zhu D, Hill AD. A new inversion method to interpret flow profiles from distributed temperature and pressure measurements in horizontal wells. SPE Prod Oper. 2009; 24: 510-21. https://doi.org/10.2118/109749-PA

Zhu S. Theoretical research on horizontal well production profile interpretation based on distributed optical fiber temperature measurement. Southwest Petroleum University; 2016.

Yoshida N. Modeling and interpretation of downhole temperature in a horizontal well with multiple fractures (Thesis). Texas A&M University; 2016. https://doi.org/10.2118/181812-MS

Luo Hongwen, Li Haitao, Liu Huibin. Prediction of temperature profile of two-phase flow fracturing horizontal well in low permeability gas reservoir. Nat Gas Geosci. 2019; 30: 389-99.

Zhai Y. Seepage mechanics. Petroleum Industry Press; 2016.

Hongwen L, Haitao L, Yongsheng T, Ying L, Beibei J, Yu L, et al. A novel inversion approach for fracture parameters and inflow rates diagnosis in multistage fractured horizontal wells. J Pet Sci Eng. 2020; 184: 106585. https://doi.org/10.1016/j.petrol.2019.106585

Hongwen L, Haitao L, Yu L, Ying L, Zhenhua G. Inversion of distributed temperature measurements to interpret the flow profile for a multistage fractured horizontal well in low-permeability gas reservoir. Appl Math Model. 2020; 77: 360-77. https://doi.org/10.1016/j.apm.2019.07.047

Luo H, Li Y, Li H, Cui X, Chen Z. Simulated annealing algorithm-based inversion model to interpret flow Rate Profiles and fracture parameters for horizontal wells in unconventional gas reservoirs. SPE J. 2021; 26(04): 1679-99. https://doi.org/10.2118/205010-PA

Creative Commons License

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

Copyright (c) 2023 Zhu Hanbin, Liu Wenqiang, Luo Hongwen, Li Haitao, Ma Hansong, Li Ying, Jiang Beibei, Xiang Yuxing, Zhang Qin

Downloads

Download data is not yet available.