(The following topics include but are not limited to)
Track 1: Artificial Intelligence
Applications of deep learning in earthquake data processing, noise reduction and imaging
Basic models and generative AI-driven intelligent seismic interpretation
Artificial intelligence-driven processing of heavy-magnetic-electric non-seismic exploration data
Physics-constrained neural networks and data-physical fusion modeling
Machine learning-assisted full waveform inversion and velocity modeling
Application of artificial intelligence in distributed optical acoustic sensing data processing
Multi-source geophysical data fusion and intelligent joint inversion
Application of neural representations and implicit neural networks in geophysical inversion
Embodied intelligent agent-driven autonomous exploration workflow
Artificial intelligence-assisted quantitative inversion of geophysical parameters and uncertainty quantification
Application of large language models and visual-language models in automatic generation of geophysical reports
Unmanned aerial vehicle geophysics and intelligent detection equipment technology
Track 2: Geophysics
New technologies for high-resolution seismic data acquisition, processing and imaging
Distributed acoustic sensing technology and its geophysical interpretation
Full waveform inversion and multi-parameter joint inversion methods
Multi-component seismic exploration and anisotropic medium research
Comprehensive interpretation of gravity, magnetic, electrical and radioactive data
Rock physics experimental analysis and inversion of underground physical parameters
Time-lapse seismic and four-dimensional seismic monitoring technology
Microseismic monitoring and induced seismic research
Well-based geophysics and comprehensive analysis of logging data
Numerical simulation of geophysical fields and high-performance computing
Urban geophysics and characterization of near-surface features
Ocean geophysics and deep-sea exploration technology
Track 3: Geological Exploration
Intelligent geological modeling and mineral exploration prediction in mining
Automatic description, evaluation and intelligent prediction of oil and gas reservoirs
Artificial intelligence-driven automatic identification of lithology and sedimentary facies
Intelligent identification and interpretation of geological structures (faults, salt domes, fractures)
Application of geostatistics and machine learning integration in mineral resource evaluation
AI applications in carbon capture, utilization and storage (CCUS) site selection and monitoring
Geological data quality control, standardization and database construction
Big data-driven regional geology and deep structure research
Risk assessment and early warning of geological disasters (landslides, earthquakes, floods)
Green exploration technology, environmental geology and sustainable development
......