IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p59-d1009956.html
   My bibliography  Save this article

Study on Shear Velocity Profile Inversion Using an Improved High Frequency Constrained Algorithm

Author

Listed:
  • Qing Ye

    (State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China)

  • Huafeng Sun

    (Cores and Samples Center of Natural Resources, China Geological Survey, Beijing 100083, China)

  • Zhiqiang Jin

    (State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China)

  • Bing Wang

    (State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China)

Abstract

The formation shear-wave (S-wave)’s velocity information around a borehole is of great importance in evaluating borehole stability, reflecting fluid invasion, and selecting perforation positions. Dipole acoustic logging is an effective method for determining a formation S-wave’s velocity radial profile around the borehole. Currently, the formation S-wave’s radial-profile inversion methods are mainly based on the impacts of radial velocity changes of formations outside the borehole on the dispersion characteristics of dipole waveforms, without considering the impacts of an acoustic tool on the dispersion curves in the inversion methods. Accordingly, the inversion accuracy is greatly impacted in practical data-processing applications. In this paper, a novel inversion algorithm, which introduces equivalent-tool theory into the shear-velocity radial profile constrained-inversion method, is proposed to obtain the S-wave’s slowness radial profile. Based on the equivalent-tool theory, the acoustic tool can be modeled using two parameters, radius and elastic modulus. The tool’s impact on the dipole waveform’s dispersion is eliminated first by using the equivalent-tool theory. Then, the corrected dispersion curve is used to carry out the constrained inversion processing. The results of this processing on the simulation data and the real logging data show the validity of the proposed algorithm.

Suggested Citation

  • Qing Ye & Huafeng Sun & Zhiqiang Jin & Bing Wang, 2022. "Study on Shear Velocity Profile Inversion Using an Improved High Frequency Constrained Algorithm," Energies, MDPI, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:59-:d:1009956
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/59/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/1/59/
    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:16:y:2022:i:1:p:59-:d:1009956. 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.