Percolation with trapping

Dias, Madalena M.; Wilkinson, David

doi:10.1088/0305-4470/19/15/034

Cited by 121 publications

(76 citation statements)

References 17 publications

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“…It has been reported that the size of the trapped clusters follows the power-law correlation in accordance with percolation theory [32,33], which is given by ( ) ∼ − , where ( ) is the number frequencies of cluster size, . The exponent, = 2.189, was reported in a previous study [34].…”

Section: Cluster Size Distributionssupporting

confidence: 65%

Pore-Scale Imaging of the Oil Cluster Dynamic during Drainage and Imbibition Using In Situ X-Ray Microtomography

Gao

Jiang

et al. 2018

Geofluids

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We imaged water-wet and oil-wet sandstones under two-phase flow conditions for different flooding states by means of X-ray computed microtomography ( CT) with a spatial resolution of 2.1 m/pixel. We systematically study pore-scale trapping of the nonwetting phase as well as size and distribution of its connected clusters and disconnected globules. We found a lower or , 19.8%, for the oil-wet plug than for water-wet plug (25.2%). Approximate power-law distributions of the water and oil cluster sizes were observed in the pore space. Besides, the value of the wetting phase gradually decreased and the nonwetting phase gradually increased during the core-flood experiment. The remaining oil has been divided into five categories; we explored the pore fluid occupancies and studied size and distribution of the five types of trapped oil clusters during different drainage stage. The result shows that only the relative volume of the clustered oil is reduced, and the other four types of remaining oil all increased. Pore structure, wettability, and its connectivity have a significant effect on the trapped oil distribution. In the water sandstone, the trapped oil tends to occupy the center of the larger pores during the water imbibition process, leading to a stable specific surface area and a gradually decreasing oil capillary pressure. Meanwhile, in oil-wet sandstone, the trapped oil blobs that tend to occupy the pores corner and attach to the walls of the pores have a large specific surface area, and the change of the oil capillary pressure was not obvious. These results have revealed the well-known complexity of multiphase flow in rocks and preliminarily show the pore-level displacement physics of the process.

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Section: Cluster Size Distributionssupporting

confidence: 65%

Pore-Scale Imaging of the Oil Cluster Dynamic during Drainage and Imbibition Using In Situ X-Ray Microtomography

Gao

Jiang

et al. 2018

Geofluids

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“…In a strongly water-wet rock we expect the water to fill areas of the pore space in order of size 39,40 , trapping disconnected ganglia in the process called snap-off. This process should be percolation like 41 so predictions can be made about the size distribution of the isolated clusters. The number n of clusters of volume s (measured in voxels) should scale as , where τ is the Fisher exponent 42 .…”

Section: Representative Resultsmentioning

confidence: 99%

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Andrew

Bijeljic

Blunt

2015

JoVE

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X-ray microtomography was used to image, at a resolution of 6.6 µm, the pore-scale arrangement of residual carbon dioxide ganglia in the pore-space of a carbonate rock at pressures and temperatures representative of typical formations used for CO 2 storage. Chemical equilibrium between the CO 2 , brine and rock phases was maintained using a high pressure high temperature reactor, replicating conditions far away from the injection site. Fluid flow was controlled using high pressure high temperature syringe pumps. To maintain representative in-situ conditions within the micro-CT scanner a carbon fiber high pressure micro-CT coreholder was used. Diffusive CO 2 exchange across the confining sleeve from the pore-space of the rock to the confining fluid was prevented by surrounding the core with a triple wrap of aluminum foil. Reconstructed brine contrast was modeled using a polychromatic x-ray source, and brine composition was chosen to maximize the three phase contrast between the two fluids and the rock. Flexible flow lines were used to reduce forces on the sample during image acquisition, potentially causing unwanted sample motion, a major shortcoming in previous techniques. An internal thermocouple, placed directly adjacent to the rock core, coupled with an external flexible heating wrap and a PID controller was used to maintain a constant temperature within the flow cell. Substantial amounts of CO 2 were trapped, with a residual saturation of 0.203 ± 0.013, and the sizes of larger volume ganglia obey power law distributions, consistent with percolation theory.

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“…It has to be stressed that our algorithm does not contain so-called trapping rules, which are commonly used in fluid flow problems. 20 Different criteria can be used to terminate the growth process: ͑1͒ ij Ͼ or ͑2͒ the cluster just spans the complete lattice ͑called breakthrough͒.…”

Section: B Percolation Algorithmsmentioning

confidence: 99%

Structure and conductivity of clusters generated by variable-range hopping percolation

et al. 2006

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Percolation with trapping

Cited by 121 publications

References 17 publications

Pore-Scale Imaging of the Oil Cluster Dynamic during Drainage and Imbibition Using In Situ X-Ray Microtomography

Pore-Scale Imaging of the Oil Cluster Dynamic during Drainage and Imbibition Using In Situ X-Ray Microtomography

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Structure and conductivity of clusters generated by variable-range hopping percolation

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