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    Quantitative Characterization of Pore Types in Laminated and Massive Oil-Bearing Shales in Qintong Sag and Jiyang Depression Using Traditional and Deep-Learning Methods

    Source: Journal of Energy Engineering:;2026:;Volume ( 152 ):;issue: 001::page 04025093-1
    Author:
    Xiong, Wu
    ,
    Yuan, Yujie
    ,
    Xie, Yibing
    ,
    Liu, Xiu
    ,
    Zhang, Dengfeng
    ,
    Zou, Jie
    DOI: 10.1061/JLEED9.EYENG-6421
    Publisher: American Society of Civil Engineers
    Abstract: AbstractQuantitative characterization of pore types in shale oil formations is crucial for the evaluation of shale oil content and mobility but is challenging. This study presents a novel integration of traditional petrophysical analyses with a U-Net deep-...Practical ApplicationsThe pore types and shapes significantly influence shale oil mobility, CO2 injectivity, and displacement efficiency. Interparticle pores demonstrate the highest porosity. Their interconnected networks form essential flow pathways for CO2 ...
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      Quantitative Characterization of Pore Types in Laminated and Massive Oil-Bearing Shales in Qintong Sag and Jiyang Depression Using Traditional and Deep-Learning Methods

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4312034
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    • Journal of Energy Engineering

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    contributor authorXiong, Wu
    contributor authorYuan, Yujie
    contributor authorXie, Yibing
    contributor authorLiu, Xiu
    contributor authorZhang, Dengfeng
    contributor authorZou, Jie
    date accessioned2026-08-20T11:19:38Z
    date available2026-08-20T11:19:38Z
    date copyright2025/11/11
    date issued2026
    identifier otherJLEED9.EYENG-6421.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312034
    description abstractAbstractQuantitative characterization of pore types in shale oil formations is crucial for the evaluation of shale oil content and mobility but is challenging. This study presents a novel integration of traditional petrophysical analyses with a U-Net deep-...Practical ApplicationsThe pore types and shapes significantly influence shale oil mobility, CO2 injectivity, and displacement efficiency. Interparticle pores demonstrate the highest porosity. Their interconnected networks form essential flow pathways for CO2 ...
    publisherAmerican Society of Civil Engineers
    titleQuantitative Characterization of Pore Types in Laminated and Massive Oil-Bearing Shales in Qintong Sag and Jiyang Depression Using Traditional and Deep-Learning Methods
    typeJournal Article
    journal volume152
    journal issue1
    journal titleJournal of Energy Engineering
    identifier doi10.1061/JLEED9.EYENG-6421
    journal fristpage04025093-1
    journal lastpage04025093-13
    page13
    treeJournal of Energy Engineering:;2026:;Volume ( 152 ):;issue: 001
    contenttypeFulltext
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