IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v166y2019icp610-623.html
   My bibliography  Save this article

Optimal scenario design of steam-assisted gravity drainage to enhance oil recovery with temperature and rate control

Author

Listed:
  • Baghernezhad, Danial
  • Siavashi, Majid
  • Nakhaee, Ali

Abstract

Steam-assisted gravity drainage (SAGD) is a commonly used thermal enhanced oil recovery (EOR) method in heavy oil reservoirs. Scenario optimizations are conducted with different optimization techniques to determine the optimal steam injection rate and temperature strategies. The performance of standard artificial bee colony (SABC), directed ABC (DABC), generalized pattern search (GPS) and mesh-adaptive direct search (MADS) algorithms were investigated. Also, the effect of initial guess and polling type on the performance of GPS and MADS were analyzed. DABC approaches the global optimum better than other employed algorithms, with a huge number of function evaluations. While, GPS is the fastest algorithm, likely to be trapped in local extrema. To eliminate this issue, the novel multi-region pattern search (MRPS) algorithm is proposed, in which the search space is divided into smaller subregions, each one is searched independently. Hence, search space is more efficiently explored and initial guess dependency is reduced. MRPS algorithm provided similar results to the DABC algorithm while lowering the computational costs up to 93%. MRPS algorithm is successfully applied for a 5-year SAGD scenario optimization. Furthermore, by scenario optimization, SAGD operation could be reduced for 1-year, providing the same NPV as that of the reference case operating for 4-years.

Suggested Citation

  • Baghernezhad, Danial & Siavashi, Majid & Nakhaee, Ali, 2019. "Optimal scenario design of steam-assisted gravity drainage to enhance oil recovery with temperature and rate control," Energy, Elsevier, vol. 166(C), pages 610-623.
    • Handle: RePEc:eee:energy:v:166:y:2019:i:c:p:610-623
    DOI: 10.1016/j.energy.2018.10.104
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218320942
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.10.104?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zuloaga, Pavel & Yu, Wei & Miao, Jijun & Sepehrnoori, Kamy, 2017. "Performance evaluation of CO2 Huff-n-Puff and continuous CO2 injection in tight oil reservoirs," Energy, Elsevier, vol. 134(C), pages 181-192.
    2. Olajire, Abass A., 2014. "Review of ASP EOR (alkaline surfactant polymer enhanced oil recovery) technology in the petroleum industry: Prospects and challenges," Energy, Elsevier, vol. 77(C), pages 963-982.
    3. Giacchetta, Giancarlo & Leporini, Mariella & Marchetti, Barbara, 2015. "Economic and environmental analysis of a Steam Assisted Gravity Drainage (SAGD) facility for oil recovery from Canadian oil sands," Applied Energy, Elsevier, vol. 142(C), pages 1-9.
    4. Pang, Zhan-xi & Wu, Zheng-bin & Zhao, Meng, 2017. "A novel method to calculate consumption of non-condensate gas during steam assistant gravity drainage in heavy oil reservoirs," Energy, Elsevier, vol. 130(C), pages 76-85.
    5. Akbilgic, Oguz & Zhu, Da & Gates, Ian D. & Bergerson, Joule A., 2015. "Prediction of steam-assisted gravity drainage steam to oil ratio from reservoir characteristics," Energy, Elsevier, vol. 93(P2), pages 1663-1670.
    6. Ezeuko, C.C. & Gates, I.D., 2018. "Thermal oil recovery from fractured reservoirs: Energy and emissions intensities," Energy, Elsevier, vol. 155(C), pages 29-34.
    7. Sun, Fengrui & Li, Chunlan & Cheng, Linsong & Huang, Shijun & Zou, Ming & Sun, Qun & Wu, Xiaojun, 2017. "Production performance analysis of heavy oil recovery by cyclic superheated steam stimulation," Energy, Elsevier, vol. 121(C), pages 356-371.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Weicheng & Vaziri, Vahid & Aphale, Sumeet S. & Dong, Shimin & Wiercigroch, Marian, 2021. "Energy saving by reducing motor rating of sucker-rod pump systems," Energy, Elsevier, vol. 228(C).
    2. Luo, Erhui & Fan, Zifei & Hu, Yongle & Zhao, Lun & Bo, Bing & Yu, Wei & Liang, Hongwei & Liu, Minghui & Liu, Yunyang & He, Congge & Wang, Jianjun, 2020. "An efficient optimization framework of cyclic steam stimulation with experimental design in extra heavy oil reservoirs," Energy, Elsevier, vol. 192(C).
    3. Mir, Hamed & Siavashi, Majid, 2022. "Whole-time scenario optimization of steam-assisted gravity drainage (SAGD) with temperature, pressure, and rate control using an efficient hybrid optimization technique," Energy, Elsevier, vol. 239(PC).
    4. Zhang, Lisong & Li, Jing & Sun, Luning & Yang, Feiyue, 2021. "An influence mechanism of shale barrier on heavy oil recovery using SAGD based on theoretical and numerical analysis," Energy, Elsevier, vol. 216(C).
    5. Asadi, Asgar & Zhang, Yaning & Mohammadi, Hassan & Khorand, Hadi & Rui, Zhenhua & Doranehgard, Mohammad Hossein & Bozorg, Mehdi Vahabzadeh, 2019. "Combustion and emission characteristics of biomass derived biofuel, premixed in a diesel engine: A CFD study," Renewable Energy, Elsevier, vol. 138(C), pages 79-89.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Jing & Zhang, Lisong & Yang, Feiyue & Sun, Luning, 2020. "Positive measure and potential implication for heavy oil recovery of dip reservoir using SAGD based on numerical analysis," Energy, Elsevier, vol. 193(C).
    2. Cheng, Linsong & Liu, Hao & Huang, Shijun & Wu, Keliu & Chen, Xiao & Wang, Daigang & Xiong, Hao, 2018. "Environmental and economic benefits of Solvent-Assisted Steam-Gravity Drainage for bitumen through horizontal well: A comprehensive modeling analysis," Energy, Elsevier, vol. 164(C), pages 418-431.
    3. Zhang, Lisong & Li, Jing & Sun, Luning & Yang, Feiyue, 2021. "An influence mechanism of shale barrier on heavy oil recovery using SAGD based on theoretical and numerical analysis," Energy, Elsevier, vol. 216(C).
    4. Mir, Hamed & Siavashi, Majid, 2022. "Whole-time scenario optimization of steam-assisted gravity drainage (SAGD) with temperature, pressure, and rate control using an efficient hybrid optimization technique," Energy, Elsevier, vol. 239(PC).
    5. Zhao, Renbao & Yu, Shuai & Yang, Jie & Heng, Minghao & Zhang, Chunhui & Wu, Yahong & Zhang, Jianhua & Yue, Xiang-an, 2018. "Optimization of well spacing to achieve a stable combustion during the THAI process," Energy, Elsevier, vol. 151(C), pages 467-477.
    6. Dong, Xiaohu & Liu, Huiqing & Chen, Zhangxin & Wu, Keliu & Lu, Ning & Zhang, Qichen, 2019. "Enhanced oil recovery techniques for heavy oil and oilsands reservoirs after steam injection," Applied Energy, Elsevier, vol. 239(C), pages 1190-1211.
    7. Liu, Hao & Cheng, Linsong & Wu, Keliu & Huang, Shijun & Maini, Brij B., 2018. "Assessment of energy efficiency and solvent retention inside steam chamber of steam- and solvent-assisted gravity drainage process," Applied Energy, Elsevier, vol. 226(C), pages 287-299.
    8. Liu, Yongge & Liu, Xiaoyu & Hou, Jian & Li, Huazhou Andy & Liu, Yueliang & Chen, Zhangxin, 2019. "Technical and economic feasibility of a novel heavy oil recovery method: Geothermal energy assisted heavy oil recovery," Energy, Elsevier, vol. 181(C), pages 853-867.
    9. Wang, H.D. & Chen, Y. & Ma, G.W., 2020. "Effects of capillary pressures on two-phase flow of immiscible carbon dioxide enhanced oil recovery in fractured media," Energy, Elsevier, vol. 190(C).
    10. Huoxin Luan & Zhaohui Zhou & Chongjun Xu & Lei Bai & Xiaoguang Wang & Lu Han & Qun Zhang & Gen Li, 2022. "Study on the Synergistic Effects between Petroleum Sulfonate and a Nonionic–Anionic Surfactant for Enhanced Oil Recovery," Energies, MDPI, vol. 15(3), pages 1-12, February.
    11. Kun Qian & Shenglai Yang & Hongen Dou & Qian Wang & Lu Wang & Yu Huang, 2018. "Experimental Investigation on Microscopic Residual Oil Distribution During CO 2 Huff-and-Puff Process in Tight Oil Reservoirs," Energies, MDPI, vol. 11(10), pages 1-16, October.
    12. Sun, Fengrui & Yao, Yuedong & Chen, Mingqiang & Li, Xiangfang & Zhao, Lin & Meng, Ye & Sun, Zheng & Zhang, Tao & Feng, Dong, 2017. "Performance analysis of superheated steam injection for heavy oil recovery and modeling of wellbore heat efficiency," Energy, Elsevier, vol. 125(C), pages 795-804.
    13. Rahmad Syah & Seyed Mehdi Alizadeh & Karina Shamilyevna Nurgalieva & John William Grimaldo Guerrero & Mahyuddin K. M. Nasution & Afshin Davarpanah & Dadan Ramdan & Ahmed Sayed M. Metwally, 2021. "A Laboratory Approach to Measure Enhanced Gas Recovery from a Tight Gas Reservoir during Supercritical Carbon Dioxide Injection," Sustainability, MDPI, vol. 13(21), pages 1-14, October.
    14. Junrong Liu & Lu Sun & Zunzhao Li & Xingru Wu, 2019. "Experimental Study on Reducing CO 2 –Oil Minimum Miscibility Pressure with Hydrocarbon Agents," Energies, MDPI, vol. 12(10), pages 1-17, May.
    15. Fengshuang Du & Bahareh Nojabaei, 2019. "A Review of Gas Injection in Shale Reservoirs: Enhanced Oil/Gas Recovery Approaches and Greenhouse Gas Control," Energies, MDPI, vol. 12(12), pages 1-33, June.
    16. Wang, Hai & Wang, Haiying & Zhu, Tong & Deng, Wanli, 2017. "A novel model for steam transportation considering drainage loss in pipeline networks," Applied Energy, Elsevier, vol. 188(C), pages 178-189.
    17. Diego Manfre Jaimes & Ian D. Gates & Matthew Clarke, 2019. "Reducing the Energy and Steam Consumption of SAGD Through Cyclic Solvent Co-Injection," Energies, MDPI, vol. 12(20), pages 1-28, October.
    18. Hong He & Jingyu Fu & Baofeng Hou & Fuqing Yuan & Lanlei Guo & Zongyang Li & Qing You, 2018. "Investigation of Injection Strategy of Branched-Preformed Particle Gel/Polymer/Surfactant for Enhanced Oil Recovery after Polymer Flooding in Heterogeneous Reservoirs," Energies, MDPI, vol. 11(8), pages 1-17, July.
    19. Huiying Zhong & Weidong Zhang & Jing Fu & Jun Lu & Hongjun Yin, 2017. "The Performance of Polymer Flooding in Heterogeneous Type II Reservoirs—An Experimental and Field Investigation," Energies, MDPI, vol. 10(4), pages 1-19, April.
    20. Rui, Zhenhua & Wang, Xiaoqing & Zhang, Zhien & Lu, Jun & Chen, Gang & Zhou, Xiyu & Patil, Shirish, 2018. "A realistic and integrated model for evaluating oil sands development with Steam Assisted Gravity Drainage technology in Canada," Applied Energy, Elsevier, vol. 213(C), pages 76-91.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:166:y:2019:i:c:p:610-623. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.