Artificial Intelligence for a Sustainable Oil and Gas Industry and Energy Transition
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".
Deadline for manuscript submissions: 20 December 2024 | Viewed by 83
Special Issue Editor
Interests: Smart Surfactants; Enhanced Oil Recovery; Sustainable Oil and Gas Development; Molecular Dynamics; Artificial Intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
At present, the oil and gas industry is undergoing a significant transformation, driven by the urgent need for sustainability and the global shift towards renewable energy sources. Artificial intelligence (AI) plays a pivotal role in this transition, offering innovative solutions to enhance efficiency, reduce the environmental impact, and optimize resource management.
This Special Issue aims to collate cutting-edge research and practical applications of AI that contribute to a more sustainable oil and gas industry and facilitate the energy transition. By leveraging AI technologies, we seek to address critical challenges and promote advancements that align with sustainability goals and the evolving energy landscape.
The topics of interest for publication include, but are not limited to, the following:
- AI-driven optimization of exploration and production processes;
- Predictive maintenance and failure prevention using AI;
- AI applications in reducing emissions and minimizing the environmental impact;
- Machine learning models for resource management and decision-making;
- AI-enhanced data analytics for improved efficiency and cost reduction;
- Integration of AI with renewable energy systems in hybrid models;
- AI in energy transition planning and policy development;
- Case studies demonstrating successful AI implementations in the oil and gas sector.
We invite authors to submit original research, reviews, and case studies that highlight the transformative potential of AI in creating a more sustainable and efficient oil and gas industry and supporting the global energy transition.
Dr. Mohammadali Ahmadi
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- machine learning
- oil and gas industry
- sustainability
- energy transition
- predictive maintenance
- environmental impact
- resource optimization
- data analytics
- renewable energy integration
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