IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i7p1723-d1623864.html
   My bibliography  Save this article

A Novel Regularization Model for Inversion of the Fracture Geometric Parameters in Hydraulic-Fractured Shale Gas Wells

Author

Listed:
  • Hongxi Li

    (Research Insitute of Geological Exploration and Development, CNPC Chuanqing Drilling Engineering Co., Ltd., Chengdu 610066, China)

  • Li Zhang

    (Research Insitute of Geological Exploration and Development, CNPC Chuanqing Drilling Engineering Co., Ltd., Chengdu 610066, China)

  • Lu Li

    (Research Insitute of Geological Exploration and Development, CNPC Chuanqing Drilling Engineering Co., Ltd., Chengdu 610066, China)

  • Bin Zhou

    (School of Sciences, Southwest Petroleum University, Chengdu 610500, China)

  • Yunjun Zhang

    (School of Physical Education, Southwest Petroleum University, Chengdu 610500, China)

  • Yu Fu

    (School of Oil and Natural Gas Engineering, Southwest Petroleum University, Chengdu 610500, China)

Abstract

The reservoir stimulation technology based on horizontal-well hydraulic fracturing has become one of the key means for efficient development of shale gas reservoir. Accurately describing the geometric shape and statistical characteristics of fractures is an indispensable key point. In this paper, a novel regularization model is proposed to inverse the fracture parameters with joint constraints of production data and microseismic data. Fractal theory is firstly introduced to model the fracture network and the geometric shape can be controlled by several parameters. Fractures are adaptive at the height in same rank and then a novel inversion model is presented based on regularization theory. An alternative iterative algorithm is presented to approximate the optimal solution. Relative errors of 4.94% and 6.78% are found with the results of two synthetic tests. The mean square relative error of the history match is about 7.73% in the test on real data. The numerical experiments show the accuracy and efficiency of the proposed model and algorithm.

Suggested Citation

  • Hongxi Li & Li Zhang & Lu Li & Bin Zhou & Yunjun Zhang & Yu Fu, 2025. "A Novel Regularization Model for Inversion of the Fracture Geometric Parameters in Hydraulic-Fractured Shale Gas Wells," Energies, MDPI, vol. 18(7), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1723-:d:1623864
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/7/1723/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/7/1723/
    Download Restriction: no
    ---><---

    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:18:y:2025:i:7:p:1723-:d:1623864. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.