Artificial Intelligence-Driven Energy Modeling and Management
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: 15 April 2026 | Viewed by 24
Special Issue Editor
Special Issue Information
Dear Colleagues,
Fossil energy, particularly oil and natural gas, remains a vital contributor to global economic and social development. However, the exploration, development, and management of oil and gas resources are becoming increasingly challenging due to the geological complexity of petroleum systems, the uncertainties associated with subsurface processes, and the growing demand for efficiency, reliability, and sustainability. Traditional modeling and management approaches often fall short in handling large-scale, heterogeneous, and multimodal data generated across the energy lifecycle. The emergence of artificial intelligence (AI) presents transformative opportunities, enabling data-driven prediction, intelligent optimization, and adaptive decision-making across a wide range of oil and gas applications.
This Special Issue aims to collect and disseminate cutting-edge research on AI-driven energy modeling and management with a special focus on petroleum systems. Contributions are encouraged that integrate AI methodologies—such as machine learning, deep learning, and knowledge graphs—with geological, geophysical, reservoir, and engineering data. By doing so, AI can enhance hydrocarbon exploration, accelerate reservoir characterization, optimize production strategies, and improve system-level energy efficiency. Additionally, AI-enabled digital twins, intelligent oilfields, and decision-support systems are expected to transform the future of oil and gas development. Topics also include the use of AI for safety and risk management in petroleum operations, as well as its role in reducing greenhouse gas emissions through energy efficiency improvement and carbon capture, utilization, and storage (CCUS). This Special Issue welcomes interdisciplinary studies that bridge AI with petroleum engineering, geoscience, and energy system management, with the ultimate goal of fostering smarter and more sustainable oil and gas solutions.
Topics of interest for publication include, but are not limited to:
- AI-driven geological and geophysical modeling for oil and gas exploration;
- Intelligent reservoir characterization, simulation, and production optimization;
- Machine learning for unconventional resources and enhanced oil recovery (EOR);
- Digital twins, knowledge graphs, and intelligent oilfield applications;
- AI for reliability, and risk management in petroleum operations;
- Data-driven forecasting for drilling, completion, and production processes;
- AI-enabled carbon capture, utilization, and storage (CCUS) solutions;
- Integration of AI with energy efficiency and emission reduction strategies.
Dr. Xiaocai Shan
Guest Editor
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
- artificial intelligence (AI)
- oil and gas exploration
- reservoir characterization and simulation
- production optimization
- knowledge graphs and digital twins
- enhanced oil recovery (EOR)
- carbon capture
- utilization and storage (CCUS)
- intelligent oilfield AI for safety, reliability, and risk management in petroleum operations
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
