Multimodality imaging of fluid saturation and chemical transport for two-phase surfactant/polymer floods in porous rocks
File(s)
Published version
Author(s)
Rovelli, Andrea
Brodie, James
Rashid, Bilal
Tay, Weparn
Pini, Ronny
Type
Journal Article
Abstract
Multicomponent, two-phase flow in porous media is a problem of practical relevance that remains difficult to study experimentally. Advanced methodologies are needed that enable the monitoring of both the saturation of each fluid phase within the pore space and the concentration of the chemical species within the fluids. We present an approach based on multimodality imaging and apply it to the case study of surfactant/polymer flooding in a sandstone for enhanced oil recovery. X-ray computed tomography and positron emission tomography (PET) are applied for the asynchronous acquisition of dynamic profiles of saturations (aqueous and oleic) and of the solute concentration within the surfactant/polymer slug, respectively. This complementary dataset enables precise investigation of the evolution of both the oil bank and the induced mixing at its rear arising from the surfactant/polymer flooding process. The dilution index, intensity of segregation and the spreading length are used to quantify the degree of mixing within the surfactant/polymer slug as a function of time from the spatial structure of the solute concentration field. Relative to the single-phase flow scenario, a threefold increase in dispersivity is observed. We demonstrate that mixing is systematically overestimated if only the PET dataset is used—highlighting the importance of implementing multimodality imaging. We also show that the advection–dispersion equation model, parameterised using the dispersivity derived from the experiments, provides reasonable estimates for the rate of both mixing and spreading.
Date Issued
2025-01
Date Acceptance
2024-12-04
Citation
Transport in Porous Media, 2025, 152 (1)
ISSN
0169-3913
Publisher
Springer
Journal / Book Title
Transport in Porous Media
Volume
152
Issue
1
Copyright Statement
© The Author(s) 2024 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
https://link.springer.com/article/10.1007/s11242-024-02146-0
Publication Status
Published
Article Number
7
Date Publish Online
2024-12-12