Brown, S. orcid.org/0000-0001-8229-8004, Gadikota, G. and Dowell, N.M. (2017) Modelling the adsorption-desorption behavior of CO2 in shales for permanent storage of CO2 and enhanced hydrocarbon extraction. In: Energy Procedia. 13th International Conference on Greenhouse Gas Control Technologies, GHGT-13, 14-18 Nov 2016, Lausanne, Switzerland. Elsevier , pp. 6942-6949.
Abstract
Increasing global need for energy security has spurred a need for enhanced oil and gas recovery from unconventional reservoirs. From a carbon cycle point of view however, enhanced hydrocarbon extraction results in higher concentrations of CO 2 in the atmosphere, which is detrimental to the environment. Coupling the potential of storing CO 2 with gas and oil recovery is one approach to limit the rise in atmospheric CO 2 concentrations while allowing for subsurface hydrocarbon recovery. Over the past few years, shale gas and oil have emerged as one of the leading contributors to overall subsurface hydrocarbon recovery. In this study, we explore the potential of combining the adsorption of CO 2 with the enhanced recovery of CH 4 , and compare the results with water which is conventionally used for hydraulic fracturing. The adsorption-desorption behaviour is accounted for using published experimental Langmuir isotherm data. The model assumes a simplified fracture shape where the flow is one-dimensional and Darcy's law is obeyed. Key performance indicators include tonnes of CO 2 injected per scm CH 4 recovered, tonnes of H 2 O injected per scm CH 4 recovered and tonnes of CO 2 sequestered per tonne of CO 2 injected.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Oct 2017 11:13 |
Last Modified: | 19 Dec 2022 13:37 |
Published Version: | https://doi.org/10.1016/j.egypro.2017.03.1836 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.egypro.2017.03.1836 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:121852 |