Advances in Measurement and Modelling Approaches Related to Flow and Storage in the Subsurface: Experimental, Simulation, and Intelligent Methods
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".
Deadline for manuscript submissions: closed (18 April 2024) | Viewed by 7868
Special Issue Editors
Interests: energy transition; special core analysis; spontaneous imbibition; machine learning; hydrogen; fractured and tight reservoirs; enhanced recovery; carbon capture utilization and storage
Special Issues, Collections and Topics in MDPI journals
2. Adjunct Professor, Faculty of Science and Technology, Department of Chemistry, Bioscience and Environmental Engineering, Chemistry University of Stavanger, 4036 Stavanger, Norway
Interests: water- and gas based enhanced oil recovery (EOR) methods; well productivity and formation damage mechanisms; CO2 storage; wettability and wettability alteration
Interests: geothermal energy; numerical modelling; multiphase flow; reservoir engineering; carbon storage leakage
Special Issue Information
Dear Colleagues,
Formations in the subsurface are of great industrial and engineering importance as they can store hydrocarbons, groundwater, CO2, hydrogen, and geothermal energy. The number and variety of applications of the subsurface have increased in recent years with the energy transition taking place. This includes enhanced recovery, repurposing reservoirs from production to storage sites for new fluids, tracking of long-term fluid and heat migration, and determination of chemicophysical interactions between fluids and the formation. In that regard, it is important to establish experimental protocols that give reproducible and representative results, recognize important experimental artifacts that affect interpretation, and develop methods that can speed up the acquisition of data compared to time-consuming traditional procedures. As more data are collected, artificial intelligence can also be used to interpret and predict behavior and parameters without pre-assuming specific relations. Physics-informed machine learning can also be applied to constrain the tuning of neural networks to match data while ensuring physical behavior. The expected main contributions of this Special Issue are novel procedures for experimental design and interpretation and the addition of experimental data that provide new insights and fill gaps in the existing literature.
Dr. Pål Østebø Andersen
Prof. Dr. Ingebret Fjelde
Dr. Yangyang Qiao
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
- novel and smart experimental methods
- chemical reactions and alteration of physical properties
- accurate parameter estimation
- experimental guidelines
- gas leakage assessment after carbon storage
- combined interpretation of large experimental datasets
- carbon capture and utilization
- wettability
- energy transition
- enhanced oil recovery
- uncertainty and sensitivity analysis
- thermal-hydraulic–mechanical–chemical coupling effects
