Applications of Artificial Intelligence in Geotechnics and Engineering Geology—2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".
Deadline for manuscript submissions: 20 August 2025 | Viewed by 126
Special Issue Editors
Interests: AI in geoscience, seismic signal processing, geophysical inversion and reservoir characterization
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent processing of complex multidimensional information in geoscience
Special Issue Information
Dear Colleagues,
In recent years, artificial intelligence technology has been widely used to monitor and provide early warning for geological disasters, as well as in geotechnical engineering and oil and gas exploration and development. Through the application of artificial intelligence, we can extract the internal laws of geological bodies from a large amount of data. Combined with the existing physical models, it can allow us to better understand the internal operation mechanisms of geological bodies. The goal of this Special Issue is to collect high-quality papers on the applications of artificial intelligence in the fields of geotechnics, engineering geology, and resource exploration. We encourage researchers from the fields of geophysics, geotechnics, signal processing, artificial intelligence, engineering geology, applied mathematics, structural geology, and other relevant areas to participate in this research topic. Topics of interest for this Special Issue include, but are not limited to, the following:
- New AI-driven approaches in geotechnics and engineering geology;
- New AI-driven approaches for resource exploration;
- AI-driven approaches for structural analysis;
- AI-driven approaches for formation evaluation;
- AI-driven approaches for reservoir characterization;
- New data-driven approaches in geological disaster monitoring and early warning;
- Complex structure imaging and inversion.
Prof. Dr. Yaojun Wang
Dr. Hanpeng Cai
Dr. Qingqing Li
Guest Editors
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Keywords
- geophysical inversion
- geophysical data interpretation
- deep learning
- reservoir characterization
- geological disaster monitoring
- formation evaluation
- complex structure imaging
- engineering geology
- geotechnics
- uncertainty analysis and quantification
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