Emerging Research and Intelligent Technologies for Reservoir Stimulation and Enhanced Oil and Gas Recovery
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Petroleum and Low-Carbon Energy Process Engineering".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 816
Editors
Interests: hydraulic fracturing; machine learning; matrix acidizing; acid fracturing; artificial intelligence; simulation
Interests: acid fracturing; geological engineering integration; fracturing fluid
Interests: rock mechanics; heat and mass transfer; fracture mechanics; rheology; interdisciplinary application of mathematics; numerical simulations related to oil and natural gas development
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the increasing global demand for efficient, sustainable and intelligent oil and gas development, reservoir stimulation and enhanced oil and gas recovery technologies are attracting growing attention from both academia and industry. In recent years, the integration of intelligent optimization, numerical simulation, advanced functional fluids and multiscale mechanism analysis has provided new opportunities for improving stimulation efficiency, reducing operational risks and promoting more sustainable oil and gas recovery processes.
This Special Issue on “Emerging Research and Intelligent Technologies for Reservoir Stimulation and Enhanced Oil and Gas Recovery” aims to cover recent advances in the development, evaluation, simulation, optimization and field application of reservoir stimulation and enhanced recovery technologies. Topics include, but are not limited to, methods and/or applications in the following areas:
- Reservoir stimulation technologies for conventional, unconventional and complex reservoirs
- Intelligent design, optimization, diagnosis and control of reservoir stimulation and enhanced recovery processes
- Development, screening, evaluation and optimization of functional fluids for reservoir stimulation and enhanced oil and gas recovery
- Fluid–rock, fluid–fluid and fluid–solid interactions in complex reservoir environments
- Artificial intelligence, machine learning, digital twins and intelligent algorithms for stimulation design, production optimization and field decision-making
- Experimental characterization, laboratory evaluation, field diagnosis and performance assessment of stimulation and enhanced recovery technologies
Integrated experimental, numerical, intelligent and field approaches for improving oil and gas recovery
Dr. Yunjin Wang
Dr. Qing Wang
Dr. Yu Peng
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 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-anonymized 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.
Keywords
- reservoir stimulation
- enhanced oil and gas recovery
- advanced materials
- artificial intelligence
- numerical simulation
- multiscale mechanisms
- construction technology
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