OIL AND GAS RESERVOIR CHARACTERISATION OF ALTYGUYI DEPOSIT, TURKMENISTAN BASED ON PROPERTY ASPECTS AND PRODUCTION RESULTS.
Published In: NED University Journal of Research, 2024, v. 21, n. 4. P. 61 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Deryaev, Annaguly 3 of 3
Abstract
This study investigated the geological structure and hydrocarbon potential of the Altyguyi field, Turkmenistan using advanced analytical techniques to optimise future extraction strategies. An indepth analysis was performed on the geological structure and hydrocarbon production potential of the oil and gas reservoirs. An integrated approach combined geochemical, geophysical and drilling data analyses. Petroleum component analysis identified diverse compounds such as asphaltenes, resins, paraffins and sulphur, indicating the field developmental potential. Geochemical analysis delineated gas and oil component concentrations across various geological formations. Hydrochemical studies of reservoir water established its nature and origin, crucial for assessing production capabilities and environmental impacts. A methodological approach was developed to utilise isotherm creation and estimate condensate content in gas reservoirs, proving valuable for forecasting and optimising production processes. The study confirmed significant hydrocarbon deposits in the Altyguyi field, highlighting its high production potential and promising development outlook. These insights are essential for devising optimal production strategies and managing oil, gas and condensate extraction effectively. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:NED University Journal of Research. 2024/12, Vol. 21, Issue 4, p61
- Document Type:Article
- Subject Area:Geography and Cartography
- Publication Date:2024
- ISSN:2304-716X
- DOI:10.35453/NEDJR-ASCN-2024-0025
- Accession Number:182043303
- Copyright Statement:Copyright of NED University Journal of Research is the property of NED University of Engineering & Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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