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Advances in Carbon Dioxide (CO2) Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS)

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: 15 January 2026 | Viewed by 555

Special Issue Editors


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Guest Editor
Petroleum Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada
Interests: miscible and immiscible processes in fractured reservoirs; microfluidic systems; diffusion/dispersion and convection mechanisms; CO2-based enhanced oil recovery and geological sequestration of greenhouse gases; production optimization; formation damage and permeability improvement; improved oil recovery from heavy oil reservoirs; interfacial phenomena; capillary pressure and 3-phase relative permeability; fluid flow in porous media; reservoir simulation; well testing; drilling and well completion; fluids transportation
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Petroleum Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada
Interests: CO2-based enhanced oil recovery; cyclic solvent injection (CSI); foamy oil flow; numerical simulation; microfluidic systems; dimensional analysis and scaling studies

Special Issue Information

Dear Colleagues,

With the growing importance of sustainable energy solutions, technologies such as Carbon Dioxide (CO2) Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS) have gained significant attention. These interconnected areas offer great potential for addressing global energy demands while minimizing environmental impact.

Injecting CO2 into reservoirs enhances oil recovery by improving fluid flow and extraction efficiency. Moreover, CCS technology is capable of capturing CO2 from industrial and energy-related sources, transporting it to geological formations, and securely storing it. The incorporation of these approaches presents unique challenges and opportunities, such as increased efficiency, reduced costs, and ensuring that the stored carbon dioxide will remain stable for a long time.

The purpose of this Special Issue is to examine recent developments, innovative methodologies, and practical applications in CO2-EOR and CCS. Contributions addressing fundamental, technological, economic, and environmental aspects are encouraged, which will provide insight into the development of sustainable practices and policies.

A wide range of topics (research articles and reviews) are welcomed, including, but not limited to, the following:

  • Innovations in CO2-EOR techniques and reservoir optimization;
  • Advances in CO2 capture technologies;
  • Geological and environmental studies on CO2 storage integrity and monitoring;
  • Integration of CO2-EOR and CCS in energy transition strategies;
  • Novel materials and processes for CO2 utilization and recycling;
  • Life cycle analysis and carbon footprint reduction in CO2-EOR and CCS projects;
  • Modeling and simulation studies for predicting CO2 transport in porous media, storage, and recovery.

Essentially, this Special Issue aims to provide a platform for researchers and industry experts to share research findings, enhance collaboration, and contribute to the global transition to cleaner energy solutions.

Prof. Dr. Farshid Torabi
Dr. Ali Cheperli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • CO2-EOR techniques and optimization
  • CO2 capture technologies and innovations
  • energy transition and integrated CO2 solutions
  • materials and processes for CO2 utilization
  • carbon footprint and life cycle assessment
  • CO2 storage in geological formations
  • CO2 transport in porous media

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Published Papers (1 paper)

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Research

18 pages, 11439 KB  
Article
Machine Learning-Driven Prediction of CO2 Solubility in Brine: A Hybrid Grey Wolf Optimizer (GWO)-Assisted Gaussian Process Regression (GPR) Approach
by Seyed Hossein Hashemi, Farshid Torabi and Paitoon Tontiwachwuthikul
Energies 2025, 18(15), 4205; https://doi.org/10.3390/en18154205 - 7 Aug 2025
Viewed by 287
Abstract
The solubility of CO2 in brine systems is critical for both carbon storage and enhanced oil recovery (EOR) applications. In this study, Gaussian Process Regression (GPR) with eight different kernels was optimized using the Grey Wolf Optimizer (GWO) algorithm to model this [...] Read more.
The solubility of CO2 in brine systems is critical for both carbon storage and enhanced oil recovery (EOR) applications. In this study, Gaussian Process Regression (GPR) with eight different kernels was optimized using the Grey Wolf Optimizer (GWO) algorithm to model this important phase behavior. Among the tested kernels, the ARD Matern 3/2 and ARD Matern 5/2 kernels achieved the highest predictive accuracies, with R2 values of 0.9961 and 0.9960, respectively, on the test data. This demonstrates superior performance in capturing CO2 solubility trends. The GWO algorithm effectively tuned the hyperparameters for all kernel configurations, while the ARD capability successfully quantified the influence of key physicochemical parameters on CO2 solubility. The outstanding performance of the ARD Matern 3/2 and ARD Matern 5/2 kernels suggests their particular suitability for modeling complex thermodynamic behaviors in brine systems. Furthermore, this study integrates fundamental thermodynamic principles into the modeling framework, ensuring all predictions adhere to physical laws while maintaining excellent accuracy (test R2 > 0.98). These results highlight how machine learning can improve CO2 injection processes, both for underground carbon storage and enhanced oil production. Full article
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