Model Order reduction for seismic imaging
Organization:
Funded by: | NWO - DeepNL - WP2 |
PhD: |  |
Supervisor: |   |
Collaboration: | Prof.dr. Jeannot Tramper - UU, Prof.dr. Marie-Colette van Lieshout - UT, Dr. Hanneke Paulssen - UU |
Description :
total project:
- Title: Monitoring the Groningen gas field
- Summary: We will monitor the changes of the Groningen gasfield that are caused by gas production with advanced mathematical, numerical, and statistical methods by modelling data of seismic wave propagation and seismicity.
Workpackage P2: Model Order reduction for seismic imaging:
Monitoring seismicity via full-waveform inversion is computationally expensive and challenging, as the high-dimensional discretization consists of several millions of degrees of freedom and we need to find the velocity and elastic structure in every element of the high-dimensional discretization; the latter makes the parameter space very large. To speed up the calculations, Model Order Reduction (MOR) can be performed. However, due to the large-scale nature of the problem, classical MOR methods become unfeasible, as they would require prohibitively large reduced spaces. Moreover, classical MOR methods are not well-suited for wave propagation problems due to slow convergence and instabilities. The goal of this project is to develop MOR methods that are well-suited for speeding up full-waveform inversion, overcoming the above-mentioned challenges.