Submit a session proposal or short course
Propose a sessionSession proposals are welcome before Oct. 31, 2022. Please submit your proposal online in the login area or send it via e-mail to firstname.lastname@example.org
Session proposals should include a title, summary, a target IAMG journal for possible follow-up full papers, and at least two names (one Chair and one Co-Chair or more).
Responsibilities for the session chairs and co-chairs will be to:
- Attract 4, 8 or 12 oral presentations + open number of poster presentations
- Review all abstracts for the session, accept for oral or posters and make recommendations to authors
- Organize the order of the presentations in the allocated time slot before June 1st, 2023
- Register to IAMG 2023 and convene the session with the co-chair.
- Accept to act as guest editor or reviewers for follow up papers from their session in IAMG journals
Until now the following sessions are proposed.
Click on the titles marked to see a descriptions.
- Reservoir Characterization and Machine Learning: From Pore to Field ScaleSuihong Song, Yuqi Wu, Mingliang Liu, Senyou AnCharacterization and modeling of subsurface reservoirs at different scales (i.e., from pore scale to field scale) is of great significance to understand inner geological structures, reveal transport mechanisms of various phenomena, predict physical properties, and forecast fluid flow in the future. In recent years, machine learning has exhibited great potential to improve the characterization and modeling accuracy of subsurface reservoirs. In the session, we welcome innovative machine learning approaches and exciting applications related to reservoir characterization and modeling of various scales. The key topics include, but are not limited to: (1) Characterization and modeling of reservoirs at the core or field scale based on traditional geostatistics; (2) Machine learning methods for geo-modeling of macro-scale reservoirs and reconstruction of micro-scale digital cores; (3) Machine learning methods for the upscaling of reservoirs from pore to field scale; (4) Machine learning methods related to the digital rock images (e.g., denoising, segmentation, and enhancement); (5) Data-driven or physics-informed methods for geophysical/flow simulation and inverse problems; (6) Application of the above methods for various fields (e.g., petroleum, mine, groundwater, CO2 storage).
- Mathematical methods and approaches for monitoring and predicting ground movementsJan Blachowski, Jörg Benndorf, Steinar EllefmoThe session focuses on topics related to theoretical and applied studies of phenomena related to the effect of mining and post-mining on their surroundings. Such as: - application of GIS, spatial statistics, machine learning and deep learning for modelling of spatial relationships in mining areas, - applied earth observations for monitoring of mining activity, - multi-source data fusion for analysis and modelling of mining areas, - assessment of mining activities to mitigate their environmental impacts, - case studies of innovative methods and applications.
Propose a short courseShort course Proposals are welcome before Oct 31, 2022. Please submit your proposal via e-mail to email@example.com
Short course proposals should include:
- The name and short CV of the instructor
- A 1-page course description summarizing the course objectives, learning outcomes and content.
- Proposed duration
- Specific needs (computer, software)