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Energies
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Recent Advances in Subsurface Sequestration of Anthropogenic Carbon Dioxide
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Recent Advances in Subsurface Sequestration of Anthropogenic Carbon Dioxide

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

Deadline for manuscript submissions: 30 October 2024 | Viewed by 2149

Special Issue Editors

Dr. Ebrahim Fathi

E-Mail Website
Guest Editor
Petroleum and Natural Gas Engineering Department, West Virginia University, Morgantown, WV 26505, USA
Interests: unconventional oil and gas reservoir development; hydraulic fracturing; carbon capture utlization and sequestration; engineered geothermal systems; artificial intelligence
Dr. Jinqing Bao

E-Mail Website
Guest Editor
School of Petroleum Engineering, Xi’an Shiyou University, Xi’an 710065, China
Interests: rock mechanics; fracture mechanics; numerical simulation; finite element method; slope engineering; underground engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Qin He

E-Mail Website
Guest Editor
General Engineering, Saint Francis University, Loretto, PA 15940, USA
Interests: reservoir modeling and simulation; reservoir engineering; drilling engineering; production engineering; economic analysis of oil and gas properties; introduction to enhanced oil recovery; environmental petroleum engineering
Dr. Salah A. Faroughi

E-Mail Website
Guest Editor
Geo-Intelligence Laboratory, Ingram School of Engineering, Texas State University, San Marcos, TX 78666, USA
Interests: data intelligence; rheology; viscoelastic fluids; complex fluids; physics-based deep learning
Special Issues, Collections and Topics in MDPI journals
Dr. Fatemeh Belyadi

E-Mail
Guest Editor
Integrated Smart Data Solutions LLC, Morgantown, WV, USA
Interests: fracture propagation; oil and gas fields; horizontal wells; shale; gas

Special Issue Information

Dear Colleagues,

Primary considerations in subsurface sequestration of anthropogenic carbon dioxide are the knowledge on gas storability of geological formation, area of review, and post-injection site care embracing risks associated with CO2 leakage and fault reactivation. Briefly, not all high-porosity formations are suitable for the permanent storage of the gas. Some of them lack a suitable storage environment that will foster physical mechanism(s) of gas trapping. The trapping is associated with fluid–fluid or fluid–solid interactions in porous media, such as dissolution, physical adsorption, or some homogeneous and heterogeneous reactions. The dissolved gas promotes density-driven natural convection of water and the related hydrodynamic instabilities; the injected gas could be transported and dispersed over large distances depending on the boundary conditions of the reservoir.  This can lead to a source of risks, e.g., leakage and/or fault reactivation, associated with CO2 storage due to presence of wells, thief zones and geological discontinuities, such as faults in the area of review.

This Special Issue highlights recent advances in subsurface sequestration of anthropogenic carbon dioxide from pre-injection to post-injection site care the topics of interest for publication include, but are not limited to:

  • Reservoir petrophysical (core characterization and correlation) analysis;
  • Reservoir petrochemical (CO2–fluid–rock interactions) characterization;
  • Regional subsurface mapping using well logs and 2D/3D seismic data;
  • CO2 storage capacity;
  • Near well bore and large-scale natural fracture mapping;
  • Drilling and completion design;
  • Geomechanical evaluation during and after CO2 injection;
  • Real field simulation of pressure and CO2 plume saturations;
  • Sensitivity analysis and uncertainty quantification;
  • Economics and life cycle analysis of CO2 sequestration;
  • Surface and subsurface CO2 monitoring and leak detection;
  • Smart fields and application of artificial intelligence.

Dr. Ebrahim Fathi
Dr. Jinqing Bao
Dr. Qin He
Dr. Salah Aldin Faroughi
Dr. Fatemeh Belyadi
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 sequestration
  • petrophysics
  • petrochemsitry
  • geomechanics
  • seismic
  • reservoir simulation
  • artificial intelligence
  • monitoring and leak detection
  • economic and societal analysis

Published Papers (2 papers)

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Research

13 pages, 2007 KiB  
Article
Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning
by Seyed Kourosh Mahjour, Jobayed Hossain Badhan and Salah A. Faroughi
Energies 2024, 17(5), 1180; https://doi.org/10.3390/en17051180 - 1 Mar 2024
Viewed by 636
Abstract
Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set [...] Read more.
Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set while reducing computational costs. A predetermined number of RGRs is selected using an integrated unsupervised machine learning (UML) framework, which includes Euclidean distance measurement, multidimensional scaling (MDS), and a deterministic K-means (DK-means) clustering algorithm. In the context of the intricate 3D aquifer CO2 storage model, PUNQ-S3, these algorithms are utilized. The UML methodology selects five RGRs from a pool of 25 possibilities (20% of the total), taking into account the reservoir quality index (RQI) as a static parameter of the reservoir. To determine the credibility of these RGRs, their simulation results are scrutinized through the application of the Kolmogorov–Smirnov (KS) test, which analyzes the distribution of the output. In this assessment, 40 CO2 injection wells cover the entire reservoir alongside the full set. The end-point simulation results indicate that the CO2 structural, residual, and solubility trapping within the RGRs and full set follow the same distribution. Simulating five RGRs alongside the full set of 25 GRs over 200 years, involving 10 years of CO2 injection, reveals consistently similar trapping distribution patterns, with an average value of Dmax of 0.21 remaining lower than Dcritical (0.66). Using this methodology, computational expenses related to scenario testing and development planning for CO2 storage reservoirs in the presence of geological uncertainties can be substantially reduced. Full article
(This article belongs to the Special Issue Recent Advances in Subsurface Sequestration of Anthropogenic Carbon Dioxide)
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17 pages, 6233 KiB  
Article
Optimization of Liquid−Liquid Mixing in a Novel Mixer Based on Hybrid SVR-DE Model
by Hao Wang, Peijian Zhou, Ting Chen, Jiegang Mou, Jiayi Cui and Huiming Zhang
Energies 2023, 16(4), 1808; https://doi.org/10.3390/en16041808 - 11 Feb 2023
Cited by 2 | Viewed by 1051
Abstract
To solve the problem of evenly mixing flocculant and sewage, a new type of two-chamber mechanical pipe mixer was numerically calculated and its working principle was studied by means of the internal flow field. The single factor numerical simulation and analysis of some [...] Read more.
To solve the problem of evenly mixing flocculant and sewage, a new type of two-chamber mechanical pipe mixer was numerically calculated and its working principle was studied by means of the internal flow field. The single factor numerical simulation and analysis of some of the structural parameters in the mixer were carried out to determine the influence of different parameters on the results. Latin hypercube sampling was used to design 100 sets of test tables for the four variables of the branch pipe diameter, sewage flow rate, the installation height of the impeller, and the angle of the deflector. The results were optimized using the SVR-DE algorithm. After optimization, the variation coefficient of export flocculant mixing uniformity was 16.02%, which was increased by 74.94% compared with the initial 63.921%. The power consumption of the impeller was reduced by 8.30%. The concentration curves of the flocculant at different positions of the outlet tube could quickly converge to the target value. Full article
(This article belongs to the Special Issue Recent Advances in Subsurface Sequestration of Anthropogenic Carbon Dioxide)
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