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Article Dans Une Revue Journal of Energy Resources Technology Année : 2019

Microscopic Determination of Remaining Oil Distribution in Sandstones With Different Permeability Scales Using Computed Tomography Scanning

Haiyuan Yang
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Jun Yao
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Wendong Wang
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Kai Zhang
Linda Luquot

Résumé

To investigate the characteristics of oil distribution in porous media systems during a high water-cut stage, sandstones with different permeability scales of 53.63 ×10-3 μm 2 and 108.11 ×10-3 μm 2 were imaged under a resolution of 4.12 μm during a water flooding process using X-ray tomography. Based on the cluster-size distribution of oil segmented from the tomography images, and through classification using the shape factor and Euler number, the transformation of the oil distribution pattern in different injection stages was studied for samples with different pore structures. In general, the distribution patterns of an oil cluster continuously change during water injection. Large connected oil clusters break off into smaller segments. For sandstones with higher permeability, which show the largest change in distribution pattern, and the remaining oil is trapped in the pores with a radius of approximately 7-12 μm. Meanwhile, some disconnected clusters merge and lead to a re-connection during the high water cut period. Whereas the pore structure becomes compact and complex, the residual non-wetting phase becomes static and is difficult to move, and thus all distribution patterns coexist during the entire displacement process, and are mainly distributed in pores with a radius of 8-12 μm. For the pore-scale entrapment characteristics of the oil phase during a high water cut period, different enhance oil recovery (EOR) methods should be considered in sandstones correspondent to each permeability scale.
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Dates et versions

hal-02319246 , version 1 (09-11-2020)

Identifiants

Citer

Yongfei Yang, Haiyuan Yang, Liu Tao, Jun Yao, Wendong Wang, et al.. Microscopic Determination of Remaining Oil Distribution in Sandstones With Different Permeability Scales Using Computed Tomography Scanning. Journal of Energy Resources Technology, 2019, 141 (9), ⟨10.1115/1.4043131⟩. ⟨hal-02319246⟩
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