4.7 Article

Pore Fractal Characteristics of Hydrate-Bearing Sands and Implications to the Saturated Water Permeability

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2019JB018721

Keywords

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Funding

  1. National Natural Science Foundation of China [41872136, 41876051]
  2. Pilot National Laboratory for Marine Science and Technology (Qingdao) [QNLM2016ORP0203]
  3. National Key Research and Development Program of China [2017YFC0307600]
  4. China Geological Survey [DD20190221]
  5. Taishan Scholar Special Experts Project [ts201712079]

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Permeability mainly governs fluid flow through hydrate-bearing sediments, and its theoretical models play a primary role in the efficiency prediction of gas recovery from hydrate reservoirs by using numerical simulators. Most of these numerical simulators rely on empirical or semiempirical permeability models largely due to the lack of suitable parameters that well quantify the evolution of pore structures. In this study, X-ray computed tomography scans are conducted on methane hydrate-bearing sands, followed by extractions of the maximal diameter and fractal dimensions for the pore space occupied by fluids. These extracted parameters, including area and volume pore-size fractal dimensions, tortuosity fractal dimension, and the area maximal pore diameter, are further extended to develop fractal theory-based models for predictions of the hydraulic tortuosity and the saturated water permeability in hydrate-bearing sands. Results show that the pore space occupied by fluids within hydrate-bearing sands is inherently fractal. The area pore-size fractal dimension decreases but the tortuosity fractal dimension changes little with increasing hydrate saturation, and the sum of these two fractal dimensions can be used to predict the volume pore-size fractal dimension. In addition, the area maximal pore diameter decreases with increasing hydrate saturation, and a semiempirical model is proposed. The fractal theory-based permeability reduction model agrees well with available experimental data, and it can capture the essential physics of saturated water permeability reduction in hydrate-bearing sediments during hydrate formation.

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