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Xu Dong
Researcher at Northeast Petroleum University
Publications - 19
Citations - 306
Xu Dong is an academic researcher from Northeast Petroleum University. The author has contributed to research in topics: Oil shale & Porous medium. The author has an hindex of 6, co-authored 16 publications receiving 130 citations. Previous affiliations of Xu Dong include Qingdao University of Science and Technology & University of Alberta.
Papers
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Journal ArticleDOI
Measurement of total porosity for gas shales by gas injection porosimetry (GIP) method
Jianmeng Sun,Xu Dong,Xu Dong,Jinjie Wang,Douglas R. Schmitt,Chunlu Xu,Tariq Mohammed,Dewen Chen +7 more
TL;DR: In this paper, the authors proposed a modified porosimeter design to meet the particular needs of gas shales, where Helium is used to minimize adsorption via the molecular sieve effect that can occur during gas shale porosity measurements.
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NMR-Based Study of the Pore Types’ Contribution to the Elastic Response of the Reservoir Rock
Naser Golsanami,Xuepeng Zhang,Weichao Yan,Linjun Yu,Huaimin Dong,Xu Dong,Likai Cui,Madusanka Nirosh Jayasuriya,Shanilka Gimhan Fernando,Ehsan Barzgar +9 more
TL;DR: In this article, the authors investigated different pore types, i.e., micro, meso, and macropores, contribution to the elastic wave velocity using the laboratory NMR and elastic experiments on coal core samples under different fluid saturations.
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How N2 injection improves the hydrocarbon recovery of CO2 HnP: An NMR study on the fluid displacement mechanisms
Xu Dong,Xu Dong,Luyi Shen,Naser Golsanami,Xuefeng Liu,Yuli Sun,Fei Wang,Ying Shi,Jianmeng Sun +8 more
TL;DR: It is found that N2 and CO2 perform similarly in the displacement of free fluids (FF), but N2 displaces little capillary bound fluids (CAF), however, replacing N2 with CO2 after a few N2 HnP cycles results in significant improvement in the recovery of CAF in the medium-sized pores than the Hnp using CO2 exclusively.
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Characterizing clay textures and their impact on the reservoir using deep learning and Lattice-Boltzmann simulation applied to SEM images
Naser Golsanami,Madusanka Nirosh Jayasuriya,Weichao Yan,Shanilka Gimhan Fernando,Xuefeng Liu,Likai Cui,Xuepeng Zhang,Qamar Yasin,Huaimin Dong,Xu Dong +9 more
TL;DR: In this paper, the authors used Scanning Electron Microscopy (SEM) images and respectively adopted deep learning for typing and quantifying clays, and the Lattice-Boltzmann Method (LBM) for flow simulations with and without the presence of clays.
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NMR characterization of a tight sand's pore structures and fluid mobility: An experimental investigation for CO2 EOR potential
Xu Dong,Xu Dong,Luyi Shen,Xuefeng Liu,Pengyun Zhang,Yuli Sun,Weichao Yan,Liming Jiang,Fei Wang,Jianmeng Sun +9 more
TL;DR: In this article, the pore size distribution and fluid movement in tight sand samples were investigated and low field NMR experiments were conducted to investigate the fluid displacements across pores of different sizes, represented by the T2 relaxation times.