IDEAS home Printed from https://ideas.repec.org/a/epw/ejeng0/v3y2018i4id60472.html

Comparative Study of Oil Production Forecast by Decline Curve Analysis and Material Balance

Author

Listed:
  • Charley Iyke Anyadiegwu

    (Federal University of Technology, Owerri (FUTO).)

  • Nnaemeka Princewill Ohia

    (Federal University of Technology, Owerri (FUTO).)

Abstract

Comparative analysis of forecast of rate of production of oil from a reservoir using decline curve analysis and material balance was presented. The data for reservoir A located Southeast, Nigeria was obtained for the study. The analysis on the well using decline curve analysis showed that the rate of production from the well over the years followed an exponential method of decline. The rate of production of the well was predicted to be 158 stb/day in 2020. The second analysis on the well was performed using material balance with MBAL. The rate of production of the well was predicted to be 411.984 stb/day in 2020. It was also read from MBAL that the well will have a constant flow rate from the 20th year to the 31st year of the producing life of the well which is 2020. It is seen that the values of rates of production gotten from the prediction analyses of the well using the two methods of analysis differ. The rate in 2020 was predicted to be 158 stb/day using decline curve analysis and 411.984 stb/day using material balance

Suggested Citation

  • Charley Iyke Anyadiegwu & Nnaemeka Princewill Ohia, 2018. "Comparative Study of Oil Production Forecast by Decline Curve Analysis and Material Balance," European Journal of Engineering and Technology Research, European Open Science, vol. 3(4), pages 19-26, April.
  • Handle: RePEc:epw:ejeng0:v:3:y:2018:i:4:id:60472
    DOI: 10.24018/ejeng.2018.3.4.472
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejeng/article/view/60472
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejeng/article/download/60472/11885
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejeng.2018.3.4.472?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:epw:ejeng0:v:3:y:2018:i:4:id:60472. 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: Support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejeng .

    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.