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Fast micro-computed tomography data of solute transport in porous media with different heterogeneity levels.


ABSTRACT: Solute transport processes are influenced by pore-scale heterogeneity. To study this, transient micron-scale solute concentration fields were imaged by fast laboratory-based X-ray micro-computed tomography. We performed tracer injection experiments in three types of porous material with increasing levels of heterogeneity (sintered glass, Bentheimer sandstone and Savonnières limestone). Different Peclet numbers were used during the experiments. For each sample and Peclet number, datasets of 40 to 74 3D images were acquired by continuous scanning with a voxel size of 13.4 to 14.6?µm and a temporal resolution of 15 to 12?seconds. To determine the measurement uncertainty on the obtained concentration fields, we performed calibration experiments under similar circumstances (temporal resolution of 12?seconds and voxel size of 13.0?µm). Here, we provide a systematic description of the data acquisition and processing and make all data, a total of 464 tomograms, publicly available. The combined dataset offers new opportunities to study the influence of pore-scale heterogeneity on solute transport, and to validate pore-scale simulations of this process in increasingly complex samples.

SUBMITTER: Van Offenwert S 

PROVIDER: S-EPMC7817660 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Fast micro-computed tomography data of solute transport in porous media with different heterogeneity levels.

Van Offenwert Stefanie S   Cnudde Veerle V   Boone Marijn M   Bultreys Tom T  

Scientific data 20210120 1


Solute transport processes are influenced by pore-scale heterogeneity. To study this, transient micron-scale solute concentration fields were imaged by fast laboratory-based X-ray micro-computed tomography. We performed tracer injection experiments in three types of porous material with increasing levels of heterogeneity (sintered glass, Bentheimer sandstone and Savonnières limestone). Different Peclet numbers were used during the experiments. For each sample and Peclet number, datasets of 40 to  ...[more]

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