IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v211y2020ics0360544220317382.html
   My bibliography  Save this article

Profound connotations of parameters on the geometric anisotropy of pores in which oil store and flow: A new detailed case study which aimed to dissect, conclude and improve the theoretical meaning and practicability of “Umbrella Deconstruction” method furtherly

Author

Listed:
  • Du, Shuheng

Abstract

“Umbrella Deconstruction” method has already been raised in a set of published papers accomplished by the author of this study and his collaborators. This method aimed to unlock the “black box” of the anisotropic pores, elements and minerals of reservoirs from a new perspective. Compared with all the previous case studies, the purpose of this study is to investigate the profound connotations and special significance of the geometric parameters describing the pores in the study of “Umbrella Deconstruction” method furtherly.

Suggested Citation

  • Du, Shuheng, 2020. "Profound connotations of parameters on the geometric anisotropy of pores in which oil store and flow: A new detailed case study which aimed to dissect, conclude and improve the theoretical meaning and," Energy, Elsevier, vol. 211(C).
  • Handle: RePEc:eee:energy:v:211:y:2020:i:c:s0360544220317382
    DOI: 10.1016/j.energy.2020.118630
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220317382
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2020.118630?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Du, Shuheng & Shi, Yongmin & Zheng, Xiaojiao & Chai, Guangsheng, 2020. "Using “Umbrella Deconstruction & Energy Dispersive Spectrometer (UD-EDS)” technique to quantify the anisotropic elements distribution of "Chang 7" shale and its significance," Energy, Elsevier, vol. 191(C).
    2. Azadeh, A. & Tarverdian, S., 2007. "Integration of genetic algorithm, computer simulation and design of experiments for forecasting electrical energy consumption," Energy Policy, Elsevier, vol. 35(10), pages 5229-5241, October.
    3. Gunde, Akshay C. & Bera, Bijoyendra & Mitra, Sushanta K., 2010. "Investigation of water and CO2 (carbon dioxide) flooding using micro-CT (micro-computed tomography) images of Berea sandstone core using finite element simulations," Energy, Elsevier, vol. 35(12), pages 5209-5216.
    4. Saif, Tarik & Lin, Qingyang & Butcher, Alan R. & Bijeljic, Branko & Blunt, Martin J., 2017. "Multi-scale multi-dimensional microstructure imaging of oil shale pyrolysis using X-ray micro-tomography, automated ultra-high resolution SEM, MAPS Mineralogy and FIB-SEM," Applied Energy, Elsevier, vol. 202(C), pages 628-647.
    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. Sun, Fuqiang & Du, Shuheng & Zhao, Ya-Pu, 2022. "Fluctuation of fracturing curves indicates in-situ brittleness and reservoir fracturing characteristics in unconventional energy exploitation," Energy, Elsevier, vol. 252(C).

    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. He, Liuyue & Xu, Zhenci & Wang, Sufen & Bao, Jianxia & Fan, Yunfei & Daccache, Andre, 2022. "Optimal crop planting pattern can be harmful to reach carbon neutrality: Evidence from food-energy-water-carbon nexus perspective," Applied Energy, Elsevier, vol. 308(C).
    2. You, Junyu & Ampomah, William & Sun, Qian, 2020. "Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework," Applied Energy, Elsevier, vol. 279(C).
    3. Muhammad Fayaz & DoHyeun Kim, 2018. "Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic," Energies, MDPI, vol. 11(1), pages 1-22, January.
    4. Verdone, Alessio & Scardapane, Simone & Panella, Massimo, 2024. "Explainable Spatio-Temporal Graph Neural Networks for multi-site photovoltaic energy production," Applied Energy, Elsevier, vol. 353(PB).
    5. Zhen-Yao Chen & R. J. Kuo, 2019. "Combining SOM and evolutionary computation algorithms for RBF neural network training," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1137-1154, March.
    6. Golberg, Alexander, 2015. "Environmental exergonomics for sustainable design and analysis of energy systems," Energy, Elsevier, vol. 88(C), pages 314-321.
    7. Yang, Min & Liu, Qi & Zhao, Hongsheng & Li, Ziqiang & Liu, Bing & Li, Xingdong & Meng, Fanyong, 2014. "Automatic X-ray inspection for escaped coated particles in spherical fuel elements of high temperature gas-cooled reactor," Energy, Elsevier, vol. 68(C), pages 385-398.
    8. Xu, Qingyang & Sun, Feihu & Cai, Qiran & Liu, Li-Jing & Zhang, Kun & Liang, Qiao-Mei, 2022. "Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China," Renewable Energy, Elsevier, vol. 190(C), pages 945-958.
    9. Shen, Peiliang & Jiang, Yi & Zhang, Yangyang & Liu, Songhui & Xuan, Dongxing & Lu, Jianxin & Zhang, Shipeng & Poon, Chi Sun, 2023. "Production of aragonite whiskers by carbonation of fine recycled concrete wastes: An alternative pathway for efficient CO2 sequestration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    10. Jin, Xu & Wang, Xiaoqi & Yan, Weipeng & Meng, Siwei & Liu, Xiaodan & Jiao, Hang & Su, Ling & Zhu, Rukai & Liu, He & Li, Jianming, 2019. "Exploration and casting of large scale microscopic pathways for shale using electrodeposition," Applied Energy, Elsevier, vol. 247(C), pages 32-39.
    11. Zhao, Li & Guanhua, Ni & Yan, Wang & Hehe, Jiang & Yongzan, Wen & Haoran, Dou & Mao, Jing, 2022. "Semi-homogeneous model of coal based on 3D reconstruction of CT images and its seepage-deformation characteristics," Energy, Elsevier, vol. 259(C).
    12. Pan, Bin & Yin, Xia & Yang, Zhengru & Ghanizadeh, Amin & Debuhr, Chris & Clarkson, Christopher R. & Gou, Feifei & Zhu, Weiyao & Ju, Yang & Iglauer, Stefan, 2024. "Real-time imaging of oil shale pyrolysis dynamics at nanoscale via environmental scanning electron microscopy," Applied Energy, Elsevier, vol. 363(C).
    13. Niu, Daming & Sun, Pingchang & Ma, Lin & Zhao, Kang'an & Ding, Cong, 2023. "Porosity evolution of Minhe oil shale under an open rapid heating system and the carbon storage potentials," Renewable Energy, Elsevier, vol. 205(C), pages 783-799.
    14. Bowen Ling & Hasan J. Khan & Jennifer L. Druhan & Ilenia Battiato, 2020. "Multi-Scale Microfluidics for Transport in Shale Fabric," Energies, MDPI, vol. 14(1), pages 1-23, December.
    15. Ren, Jitian & Xiao, Wenlian & Pu, Wanfen & Tang, Yanbing & Bernabé, Yves & Cheng, Qianrui & Zheng, Lingli, 2024. "Characterization of CO2 miscible/immiscible flooding in low-permeability sandstones using NMR and the VOF simulation method," Energy, Elsevier, vol. 297(C).
    16. Li, Fengyun & Zheng, Haofeng & Li, Xingmei & Yang, Fei, 2021. "Day-ahead city natural gas load forecasting based on decomposition-fusion technique and diversified ensemble learning model," Applied Energy, Elsevier, vol. 303(C).
    17. Aydin, Gokhan, 2014. "Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 382-389.
    18. Wang, Lian & Yao, Yuedong & Wang, Kongjie & Adenutsi, Caspar Daniel & Zhao, Guoxiang & Lai, Fengpeng, 2022. "Hybrid application of unsupervised and supervised learning in forecasting absolute open flow potential for shale gas reservoirs," Energy, Elsevier, vol. 243(C).
    19. Qiao, Weibiao & Liu, Wei & Liu, Enbin, 2021. "A combination model based on wavelet transform for predicting the difference between monthly natural gas production and consumption of U.S," Energy, Elsevier, vol. 235(C).
    20. Zheng, Peng & Xia, Yucheng & Yao, Tingwei & Jiang, Xu & Xiao, Peiyao & He, Zexuan & Zhou, Desheng, 2022. "Formation mechanisms of hydraulic fracture network based on fracture interaction," Energy, Elsevier, vol. 243(C).

    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:eee:energy:v:211:y:2020:i:c:s0360544220317382. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.