IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i20p6461-d652531.html
   My bibliography  Save this article

Conditions for Effective Application of the Decline Curve Analysis Method

Author

Listed:
  • Dmitriy A. Martyushev

    (Department of Oil and Gas Technologies, Perm National Research Polytechnic University, 614990 Perm, Russia)

  • Inna N. Ponomareva

    (Department of Oil and Gas Technologies, Perm National Research Polytechnic University, 614990 Perm, Russia)

  • Vladislav I. Galkin

    (Department of Oil and Gas Geology, Perm National Research Polytechnic University, 614990 Perm, Russia)

Abstract

Determining the reliable values of the filtration parameters of productive reservoirs is the most important task in monitoring the processes of reserve production. Hydrodynamic studies of wells by the pressure build-up method, as well as a modern method based on production curve analysis (Decline Curve Analysis (DCA)), are some of the effective methods for solving this problem. This paper is devoted to assessing the reliability of these two methods in determining the filtration parameters of terrigenous and carbonaceous productive deposits of oil fields in the Perm Krai. The materials of 150 conditioned and highly informative (obtained using high-precision depth instruments) studies of wells were used to solve this problem, including 100 studies conducted in terrigenous reservoirs (C 1 v) and 50 carried out in carbonate reservoirs (C 2 b). To solve the problem, an effective tool was used—multivariate regression analysis. This approach is new and has not been previously used to assess the reliability of determining the filtration parameters of reservoir systems by different research methods. With its use, a series of statistical models with varying degrees of detail was built. A series of multivariate mathematical models of well flow rates using the filtration parameters determined for each of the methods is constructed. The inclusion or non-inclusion of these filtration parameters in the resulting flow rate models allows us to give a reasonable assessment of the possibility of using the pressure build-up method and the DCA method. All the constructed models are characterized by high statistical estimates: in all cases, a high value of the determination coefficient was obtained, and the probability of an error in all cases was significantly less than 5%. As applied to the fields under consideration, it was found that both methods demonstrate stable results in terrigenous reservoirs. The permeability determined by the DCA method and the pressure build-up curve does not control the flow of the fluid in carbonate reservoirs, which proves the complexity of the filtration processes occurring in them. The DCA method is recommended for use to determine the permeability and skin factor in the conditions of terrigenous reservoirs.

Suggested Citation

  • Dmitriy A. Martyushev & Inna N. Ponomareva & Vladislav I. Galkin, 2021. "Conditions for Effective Application of the Decline Curve Analysis Method," Energies, MDPI, vol. 14(20), pages 1-10, October.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6461-:d:652531
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/20/6461/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/20/6461/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruud Weijermars & Kiran Nandlal, 2020. "Pre-Drilling Production Forecasting of Parent and Child Wells Using a 2-Segment Decline Curve Analysis (DCA) Method Based on an Analytical Flow-Cell Model Scaled by a Single Type Well," Energies, MDPI, vol. 13(6), pages 1-27, March.
    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. Taha Yehia & Ahmed Naguib & Mostafa M. Abdelhafiz & Gehad M. Hegazy & Omar Mahmoud, 2023. "Probabilistic Decline Curve Analysis: State-of-the-Art Review," Energies, MDPI, vol. 16(10), pages 1-20, May.

    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. David Waters & Ruud Weijermars, 2021. "Predicting the Performance of Undeveloped Multi-Fractured Marcellus Gas Wells Using an Analytical Flow-Cell Model (FCM)," Energies, MDPI, vol. 14(6), pages 1-42, March.
    2. Ruud Weijermars, 2020. "Optimization of Fracture Spacing and Well Spacing in Utica Shale Play Using Fast Analytical Flow-Cell Model (FCM) Calibrated with Numerical Reservoir Simulator," Energies, MDPI, vol. 13(24), pages 1-24, December.

    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:14:y:2021:i:20:p:6461-:d:652531. 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.