High-performance computing is in continuous evolution driven be the fast-growing applications of machine learning and artificial intelligence. At the hardware level General Purpose Graphical Processing Units (GPGPU) have been widely adopted and new specifically designed AI chips start to have an impact on applications. At the system level, cloud and edge computing are replacing on-premises HPC systems.

This explosive growth creates great uncertainty on which, among all the possible modern HPC architectures, best fits the computational needs of Earth Sciences. Furthermore, taking full advantage of these architectures will require more than a simple adaptation of existing algorithms to new hardware; it will require the design of new numerical algorithms and the development of new programming models that enable fast and efficient implementation.

SESAAI goal is to help the industry to take full advantage new computational technologies by supporting the development of new ideas that  are required for achieving ambitious goals such as the deployment of subsurface digital twins that fully couple advanced modeling with the data flow generated by modern fiber-sensing systems.

Research Activities

The goals of SESAAI are to:

• Evaluate modern High-Performance Computing (HPC) architectures for seismic-imaging algorithms and for modeling coupled fluid-flow/geomechanics phenomena in the subsurface.
• Develop new physics-based and data-driven algorithms that take advantage of modern HPC architectures.
• Influence the future technological offering by Information Technology (IT) companies to better meet needs of subsurface modeling, imaging, and monitoring.