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An X-ray computed micro-tomography dataset for oil removal from carbonate porous media
- Source :
- Scientific Data, Pak, T, Archilha, N L, Mantovani, I F, Moreira, A C & Butler, I B 2019, ' An X-ray computed micro-tomography dataset for oil removal from carbonate porous media ', Scientific Data, vol. 6, pp. 190004 . https://doi.org/10.1038/sdata.2019.4
- Publication Year :
- 2018
-
Abstract
- This study reveals the pore-scale details of oil mobilisation and recovery from a carbonate rock upon injection of aqueous nanoparticle (NP) suspensions. X-ray computed micro-tomography (μCT), which is a non-destructive imaging technique, was used to acquire a dataset which includes: (i) 3D images of the sample collected at the end of fluid injection steps, and (ii) 2D radiogram series collected during fluid injections. The latter allows monitoring fluid flow dynamics at time resolutions down to a few seconds using a laboratory-based μCT scanner. By making this dataset publicly available we enable (i) new image reconstruction algorithms to be tested on large images, (ii) further development of image segmentation algorithms based on machine learning, and (iii) new models for multi-phase fluid displacements in porous media to be evaluated using images of a dynamic process in a naturally occurring and complex material. This dataset is comprehensive in that it offers a series of images that were captured before/during/and after the immiscible fluid injections.
- Subjects :
- Statistics and Probability
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Data Descriptor
010504 meteorology & atmospheric sciences
Mineralogy
Imaging techniques
Library and Information Sciences
01 natural sciences
Education
law.invention
Crude oil
03 medical and health sciences
chemistry.chemical_compound
law
X ray computed
Fluid dynamics
Radiogram
030304 developmental biology
0105 earth and related environmental sciences
0303 health sciences
Micro tomography
Sample (graphics)
Computer Science Applications
Environmental sciences
chemistry
Carbonate
Statistics, Probability and Uncertainty
Porous medium
Geology
Information Systems
Subjects
Details
- ISSN :
- 20524463
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- Scientific data
- Accession number :
- edsair.doi.dedup.....d894f45802014bfdff2e0432f33c6c29
- Full Text :
- https://doi.org/10.1038/sdata.2019.4