IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i16p4202-d398946.html
   My bibliography  Save this article

Study on Well Selection Method for Refracturing Horizontal Wells in Tight Reservoirs

Author

Listed:
  • Qihong Feng

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

  • Jiawei Ren

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

  • Xianmin Zhang

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

  • Xianjun Wang

    (Daqing Oilfield Company Limited Production Technology Institute, Daqing 163000, China)

  • Sen Wang

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

  • Yurun Li

    (School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China)

Abstract

Refracturing technology is one of the key technologies to recover the productivity of horizontal wells in tight oil reservoirs, and the selection of best candidate wells from target blocks is the basis of this technology. Based on the refracturing production database, this paper analyzes the direct relationship between geological data, initial fracturing completion data, and dynamic production data, and the stimulation effect of refracturing. Considering the interaction among multiple factors, the factors affecting the stimulation effect of refracturing are classified and integrated, and a comprehensive index including geology, engineering, and production is constructed, making this index meaningful both for physical and engineering properties. The XGBoost decision tree model is established to analyze the weight of influence for the comprehensive index of geology, engineering, and production in predicting the stimulation effect of refracturing. A comprehensive decision index of refracturing well selection is formed by combining the above three for performing a fast selection of horizontal candidate wells for fracturing. Taking a horizontal well test area in Songliao Basin as an example, the target wells of refracturing are selected by this method, and field operation is carried out, and a good stimulation effect is achieved. The results show that the comprehensive decision-making index constructed by this method is reliable and has certain guiding significance for well selection and stimulation potential evaluation of tight oil reservoir.

Suggested Citation

  • Qihong Feng & Jiawei Ren & Xianmin Zhang & Xianjun Wang & Sen Wang & Yurun Li, 2020. "Study on Well Selection Method for Refracturing Horizontal Wells in Tight Reservoirs," Energies, MDPI, vol. 13(16), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4202-:d:398946
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/16/4202/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/16/4202/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fanhui Zeng & Xiaozhao Cheng & Jianchun Guo & Liang Tao & Zhangxin Chen, 2017. "Hybridising Human Judgment, AHP, Grey Theory, and Fuzzy Expert Systems for Candidate Well Selection in Fractured Reservoirs," Energies, MDPI, vol. 10(4), pages 1-22, April.
    2. Kiran Nandlal & Ruud Weijermars, 2019. "Impact on Drained Rock Volume (DRV) of Storativity and Enhanced Permeability in Naturally Fractured Reservoirs: Upscaled Field Case from Hydraulic Fracturing Test Site (HFTS), Wolfcamp Formation, Midl," Energies, MDPI, vol. 12(20), pages 1-36, October.
    3. Zhou Zhou & Shiming Wei & Rong Lu & Xiaopeng Li, 2020. "Numerical Study on the Effects of Imbibition on Gas Production and Shut-In Time Optimization in Woodford Shale Formation," Energies, MDPI, vol. 13(12), pages 1-18, June.
    4. Tengfei Wang & Jiexiang Wang, 2019. "Catalytic Effect of Cobalt Additive on the Low Temperature Oxidation Characteristics of Changqing Tight Oil and Its SARA Fractions," Energies, MDPI, vol. 12(15), pages 1-21, July.
    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. Xianmin Zhang & Jiawei Ren & Qihong Feng & Xianjun Wang & Wei Wang, 2021. "Prediction of Refracturing Timing of Horizontal Wells in Tight Oil Reservoirs Based on an Integrated Learning Algorithm," Energies, MDPI, vol. 14(20), pages 1-16, October.

    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. Lefeng Cheng & Tao Yu & Guoping Wang & Bo Yang & Lv Zhou, 2018. "Hot Spot Temperature and Grey Target Theory-Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study," Energies, MDPI, vol. 11(1), pages 1-26, January.
    2. Weixin Yang & Lingguang Li, 2017. "Efficiency Evaluation and Policy Analysis of Industrial Wastewater Control in China," Energies, MDPI, vol. 10(8), pages 1-18, August.
    3. Dianfa Wu & Zhiping Yang & Ningling Wang & Chengzhou Li & Yongping Yang, 2018. "An Integrated Multi-Criteria Decision Making Model and AHP Weighting Uncertainty Analysis for Sustainability Assessment of Coal-Fired Power Units," Sustainability, MDPI, vol. 10(6), pages 1-27, May.
    4. Truong Quang Dinh & James Marco & Hui Niu & David Greenwood & Lee Harper & David Corrochano, 2017. "A Novel Method for Idle-Stop-Start Control of Micro Hybrid Construction Equipment—Part B: A Real-Time Comparative Study," Energies, MDPI, vol. 10(9), pages 1-25, August.
    5. Truong Quang Dinh & James Marco & Hui Niu & David Greenwood & Lee Harper & David Corrochano, 2017. "A Novel Method for Idle-Stop-Start Control of Micro Hybrid Construction Equipment—Part A: Fundamental Concepts and Design," Energies, MDPI, vol. 10(7), pages 1-24, July.
    6. Reza Rezaee, 2022. "Editorial on Special Issues of Development of Unconventional Reservoirs," Energies, MDPI, vol. 15(7), pages 1-9, April.
    7. Enwen Li & Linong Wang & Bin Song & Siliang Jian, 2018. "Improved Fuzzy C-Means Clustering for Transformer Fault Diagnosis Using Dissolved Gas Analysis Data," Energies, MDPI, vol. 11(9), pages 1-17, September.
    8. Wang, Anlun & Chen, Yinghe & Wei, Jianguang & Li, Jiangtao & Zhou, Xiaofeng, 2023. "Experimental study on the mechanism of five point pattern refracturing for vertical & horizontal wells in low permeability and tight oil reservoirs," Energy, Elsevier, vol. 272(C).
    9. Elaheh Yadegaridehkordi & Mehrbakhsh Nilashi & Liyana Shuib & Shahla Asadi & Othman Ibrahim, 2019. "Development of a SaaS Adoption Decision-Making Model Using a New Hybrid MCDM Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(06), pages 1845-1874, November.
    10. Qitao Zhang & Wenchao Liu & Jiaxin Wei & Arash Dahi Taleghani & Hai Sun & Daobing Wang, 2022. "Numerical Simulation Study on Temporary Well Shut-In Methods in the Development of Shale Oil Reservoirs," Energies, MDPI, vol. 15(23), pages 1-24, December.
    11. Hossain, Sabbir & Dehghanpour, Hassan, 2024. "A theory to model pseudo steady state water production and predict long-term water recovery from fractured reservoirs," Energy, Elsevier, vol. 288(C).
    12. Li, Shoujun & Miao, Yanzi & Li, Guangyu & Ikram, Muhammad, 2020. "A novel varistructure grey forecasting model with speed adaptation and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 172(C), pages 45-70.
    13. Lin He & Chang-Ling Li & Qing-Yun Nie & Yan Men & Hai Shao & Jiang Zhu, 2017. "Core Abilities Evaluation Index System Exploration and Empirical Study on Distributed PV-Generation Projects," Energies, MDPI, vol. 10(12), pages 1-18, December.
    14. Lefeng Cheng & Tao Yu, 2018. "Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey," Energies, MDPI, vol. 11(4), pages 1-69, April.

    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:gam:jeners:v:13:y:2020:i:16:p:4202-:d:398946. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.