Hu, Z, Gao, H, Ramisetti, S orcid.org/0000-0002-2927-5257 et al. (4 more authors) (2019) Carbon Quantum Dots with Tracer-like Breakthrough Ability for Reservoir Characterisation. Science of the Total Environment, 669. pp. 579-589. ISSN 0048-9697
Abstract
Predictions have shown that our demand for oil and gas will continue to grow in the next decade, and future supply will become more reliant on tertiary recovery and from nonconventional resources. However, current reservoir characterization methodologies, such as well logs, cross-well electromagnetic imaging and seismic methods, have their individual limitations on detection range and resolution. Here we propose a pioneering way to use carbon quantum dots (CQDs) as nanoparticle tracers, which can be transported through a reservoir functioning as conventional tracers, while acting as sensors to obtain useful information. These hydrothermally produced CQDs from Xylose possess excellent stability in high ionic strength solutions, durable absorbance and fluorescence ability due to multi high-polarity functional group on their surfaces. Consistency between our on-line ultraviolet–visible (UV–Vis) spectroscopy and off-line Confocal laser scanning microscopy (CLSM) measurements confirms that CQDs have the tracer-like migration capability in glass beads-packed columns and sandstone cores, regardless of particle concentration and ionic strength. However, their migration ability is undermined in the column packed with crushed calcite grains with positive charge. We also demonstrate that quantitative oil saturation detection in unknown sandstone core samples can be achieved by such CQDs based on its breakthrough properties influenced by the presence of oil phase.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Elsevier B.V.. This is an author produced version of a paper published in Science of The Total Environment. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Quantum dots; Transport behaviour; High salinity; Subsurface reservoir characterization; Scalable nanotracer |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Institute for Applied Geosciences (IAG) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Apr 2019 11:51 |
Last Modified: | 02 Mar 2020 01:39 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.scitotenv.2019.03.007 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144756 |