JFES 2020 Virtual Semiar was successfully held on 4-5th November, 2020. Over 70 attendees enjoyed discussions on various topics such as porosity estimation workflow and machine learning application for reservoir characterization.
- Date & Time
- 4-5th Nov, 2020, 15:00-17:00 (Online seminar), 17:00-17:30 (Networking time)
- Venue
- Online
- Day 1 (4th Nov)
- 15:00-15:40
- Possibility and Characteristics of CO2-based Fracturing in Granite from Conventional to Superhot Geothermal Conditions
- Eko Pramudyo, Tohoku University Graduate School of Environmental Studies
- 15:40-16:20
- Porosity Complexity in carbonate reservoirs *Japanese
- Jiro Asada, Principal Geologist, Technology Promotion Department, INPEX Solutions, LTD
- 16:20-17:00
- Simultaneous estimation of in situ porosity and thermal structure from core sample measurements and resistivity log data *Japanese
- Suguru YABE, Researcher / Geological Survey of Japan, AIST
- 17:00-17:30 Networking
- Day 2 (5th Nov)
- 15:00-15:40
- Using machine learning to build detailed facies models at the basin & reservoir scale: Overcoming challenges in data quality to build more reliable & diverse training models.
- Kian Wei Tan, Technical Consultant, Halliburton
- 15:40-16:20
- Machine Learning-based Rock Type Classification Approach for Reservoir Distribution in Tensleep Formation.
- Lilik T. Hardanto, Application Geoscientist, Emerson Automation Solutions.
- 16:40-17:00
- Uncertainty and Spatial Modelling. Making ML and Geostatistics work together
- Colin Daly, Advisor Property Modeling, Schlumberger Limited.
- 17:00-17:30 Networking
