Intelligent Reservoir Characterization Technology and Numerical Simulation

Dear Colleagues,

The development of energy exploration and production technologies has long been a global focus, as energy serves as a core driver of modern society. Currently, against the backdrop of the global energy structure transition and carbon neutrality goals, the sustainable development of oil and gas resources is not only crucial for energy security but also closely linked to environmental protection, efficient resource utilization, and economic benefits. At the same time, the future of energy systems increasingly emphasizes emerging fields such as carbon capture, utilization, and storage (CCUS) and hydrogen energy, which are key components in building a clean, low-carbon, safe, and efficient energy system. With the rapid development of artificial intelligence, big data, and high-performance computing, intelligent reservoir characterization and numerical simulation have become cutting-edge directions in traditional oil and gas, CCUS, and hydrogen-related geology, providing critical technological support for the digital and intelligent transformation of the energy industry.

This Special Issue, "Intelligent Reservoir Characterization Technology and Numerical Simulation", will focus on core methodological advancements in this field, particularly intelligent reservoir characterization techniques and numerical simulation methods. We encourage submissions exploring the application of intelligent algorithms in reservoir characterization, high-precision numerical simulation methods and algorithms, multi-physics coupling technologies, and data-driven integration with physical models, aiming to advance the characterization and simulation of subsurface resources toward greater precision, intelligence, and efficiency.

Topics of interest for this Special Issue include, but are not limited to, the following:

1. Intelligent reservoir characterization methods and technologies;
2. High-precision numerical simulation algorithms for complex geological conditions;
3. Reservoir simulation theories and methods under multi-physics coupling;
4. Data-physical model collaborative-driven reservoir prediction techniques;
5. Intelligent methods for characterization and CO₂ migration simulation of carbon storage target formations;
6. Multi-scale intelligent characterization and flow simulation technologies for unconventional reservoirs.

We cordially invite you to submit original research articles, reviews, or case studies to share your innovative findings and insights in this field. Thank you for your attention and support for this Special Issue.

Sincerely,

Prof. Dr. Zhuwen Wang
Prof. Dr. Min Xiang
Guest Editors

Dr. Jian Lei
Guest Editor Assistant

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 250 words) can be sent to the Editorial Office for assessment.

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. Processes 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 2400 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.