IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i10p4215-d1151655.html
   My bibliography  Save this article

Estimation of Petrophysical Parameters of Carbonates Based on Well Logs and Laboratory Measurements, a Review

Author

Listed:
  • Marek Stadtműller

    (Oil and Gas Institute-National Research Institute, ul. Lubicz 25A, 31-503 Krakow, Poland)

  • Jadwiga A. Jarzyna

    (Faculty of Geology Geophysics and Environmental Protection, AGH University of Krakow, al. Mickiewicza 30, 30-059 Krakow, Poland)

Abstract

The purpose of this review paper is to show the possibilities of carbonate reservoir characterization using well logging and laboratory measurements. Attention was focused on standard and new methods of well logging acquisition and interpretation including laboratory experiments to show a part of the history of carbonate rock investigations as hydrocarbon or water reservoirs. Brief information on the geology, mineralogy and petrography of carbonate rocks was delivered. Reservoir properties, i.e., porosity (including fracturing), permeability, and saturation, were defined to emphasize the specific features of carbonates, such as fractures, and vugs. Examples of methodologies were selected from the commonly used laboratory techniques (thin sections examination, mercury and helium porosimetry, X-ray diffraction—XRD) combined with the standard well logs (bulk density—RHOB, neutron porosity—NPHI, sonic slowness—DT, and deep resistivity—Rd) to show the methods that have been used since the very beginning of the scientific and engineering studies of carbonates. Novelty in well logging, i.e., resistivity and acoustic imaging, nuclear magnetic resonance–NMR, dipole shear sonic imaging–DSI, and a spectral neutron-gamma log-geochemical device–GLT combined with modern laboratory investigations (NMR laboratory experiments, scanning electron microscopy SEM), showed how continuous information on mineral composition, porosity and saturation could be obtained and juxtaposed with very detailed laboratory data. Computed X-ray tomography (CT) enabling the 2D and 3D analyses of pores and fractures was presented as a quantitative methodology, effective in pore space characterization, revealing rock filtration abilities. Deep learning and artificial intelligence were used for joining various types of data. It was shown that thanks to new computational technologies original data from very small samples (micro scale), extensively describing the flow ability of the reservoir, could be extended to mezzo scale (core samples) and macro scale (well log images). Selected examples from the published papers illustrated the review. References cited in the text, together with the issues included in them, were the rich source of the practical knowledge processed These were checked by the authors and could be used in other projects.

Suggested Citation

  • Marek Stadtműller & Jadwiga A. Jarzyna, 2023. "Estimation of Petrophysical Parameters of Carbonates Based on Well Logs and Laboratory Measurements, a Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4215-:d:1151655
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/10/4215/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/10/4215/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jadwiga A. Jarzyna & Stanisław Baudzis & Mirosław Janowski & Edyta Puskarczyk, 2021. "Geothermal Resources Recognition and Characterization on the Basis of Well Logging and Petrophysical Laboratory Data, Polish Case Studies," Energies, MDPI, vol. 14(4), pages 1-26, February.
    2. Marek Stadtműller & Paulina I. Krakowska-Madejska & Grzegorz Leśniak & Jadwiga A. Jarzyna, 2021. "Characterization of the Carbonate Formation Fracture System Based on Well Logging Data and Results of Laboratory Measurements," Energies, MDPI, vol. 14(19), pages 1-24, September.
    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. Weronika Kaczmarczyk-Kuszpit & Krzysztof Sowiżdżał, 2024. "Integration of Well Logging and Seismic Data for the Prognosis of Reservoir Properties of Carbonates," Energies, MDPI, vol. 17(2), pages 1-15, January.
    2. Nafees Ali & Xiaodong Fu & Jian Chen & Javid Hussain & Wakeel Hussain & Nosheen Rahman & Sayed Muhammad Iqbal & Ali Altalbe, 2024. "Advancing Reservoir Evaluation: Machine Learning Approaches for Predicting Porosity Curves," Energies, MDPI, vol. 17(15), pages 1-22, July.

    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. Sławomir Kurpaska & Mirosław Janowski & Maciej Gliniak & Anna Krakowiak-Bal & Urszula Ziemiańczyk, 2021. "The Use of Geothermal Energy to Heating Crops under Cover: A Case Study of Poland," Energies, MDPI, vol. 14(9), pages 1-25, May.
    2. Stanisław Baudzis & Joanna Karłowska-Pik & Edyta Puskarczyk, 2021. "Electrofacies as a Tool for the Prediction of True Resistivity Using Advanced Statistical Methods—Case Study," Energies, MDPI, vol. 14(19), pages 1-18, September.

    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:2023:i:10:p:4215-:d:1151655. 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.