ERL Annual Founding Members Meeting 2023: New Subsurface Technologies, Inference, and Machine Learning Methods

May 23, 2023 (All day) to May 24, 2023 (All day)

Speaker: 

ERL Researchers

Each year the MIT Earth Resources Laboratory invites employees of our Founding Member companies to the MIT campus for presentations about our latest research and networking opportunities. This year’s meeting will take place 5/23-5/24 and the theme will be New Subsurface Technologies, Inference, and Machine Learning Methods. Invitations were sent to our alumni and employees of our Founding Member companies in April-- if you didn't receive yours, please contact erl-info@mit.edu.

In addition to talks by ERL students, postdocs, and research scietists, this year's meeting will feature special talks by two of MIT's leading AI researchers: Prof. Tomaso Poggio, director or the MIT Center for Brains, Minds, and Machines, and Prof. Youssef Marzouk, co-director of the MIT Center for Computational Science and Engineering.

The technical talks will take place in building 66, room 110. The cruise will leave from the MIT sailing pavilion. The members' lunch will take place in building 54, room 209.

Printable Agenda

Zoom Link

Slides

Agenda (subject to change):

Tuesday, May 23 66-110 9:00 9:20   Laurent Demanet Welcome
9:20 9:40 Induced Seimicity, CO2 Storage Lluís Saló-Salgado Evaluation of Fault Zone CO2 Migration Hazard in Geologic Carbon Sequestration 
9:40 10:00 Hilary Chang Ambient noise subsurface structure imaging for investigating site effects of induced earthquakes
10:00 10:20 Yury Akhimenkov Modeling of induced seismicity
using High-Performance Computing
10:20 10:50 Break    
10:50 11:10 Rock Physics, Geomechanics Eve Meltzer A Micro-Mechanical Analysis of
Vitrified Rock for use in Enhanced Geothermal Energy
11:10 11:30 Majed Almubarak Effects of Experimental Conditions on Fracture Research Using 3D Printed Materials
11:30 11:50 Tiange Xing Characterizing Transient
Brittle Creep by Ultrasonic Pulsing
11:50 1:30 Lunch    
1:30 2:20 Plenary Session: Deep Learning Tomaso Poggio Why do some neural networks work as well as they do?
2:20 2:40 Scientific Machine Learning Laurent Demanet Generative AI and geophysics
2:40 3:00 Matt Li SymAE for Redatuming Nuisance Variations in
Real World Datasets
3:00 3:20 Borjan Geshkovski Understanding redatuming with symmetric autoencoders using matrix completion
3:20 3:50 Break    
3:50 4:10 Scientific machine learning, CO2 storage Brindha Kanniah Symmetric autoencoders for deepwater static correction. 
4:10 4:30 Hannah Lu Uncertainty Quantification of CO2 Leakage and Risk Analysis of Induced Seismicity for Large-scale Geological CO2 Sequestration
MIT Sailing Pavilion 6:00 9:00 River/Harbor Dinner Cruise    
Wednesday, May 24 66-110 9:30 10:20 Plenary Session: Uncertainty Quantification Youssef Marzouk Solving Bayesian inverse problems with transport: structured and amortized inference
10:20 10:40 Geothermal, Field Data Ben Holtzman Towards *deep* crustal heat mining:
Potentials and (thermo-mechanical) problems
10:40 11:00 Malcolm White Seismotectonics and energy
production in the Salton Sea Geothermal Field
11:00 11:20 Aime Fournier Study of covariance across Volve field data
54-209 12:00 2:00 ERL Members Lunch