KAUST and Cerebras Systems collaborated on multi-dimensional seismic processing using the Condor Galaxy AI supercomputer, achieving record sustained memory bandwidth of 92.58 petabytes per second. They developed a Tile Low-Rank Matrix-Vector Multiplication (TLR-MVM) kernel to exploit the architecture of Cerebras CS-2 systems. This work was recognized as a finalist for the 2023 Gordon Bell Prize. Why it matters: This demonstrates the potential of AI-customized architectures for seismic processing, with broader implications for climate modeling and other scientific domains in the region and globally.
KAUST Ph.D. students Kai Lu and Yuqing Chen won Best Presentation awards at a Society of Exploration Geophysicists workshop in Beijing. Lu's research focuses on machine learning applications in seismic processing, while Chen uses machine learning for automated semblance spectrum picking. They both leverage KAUST's Shaheen II supercomputer for their work. Why it matters: This highlights the increasing role of AI and ML in the oil and gas industry, and KAUST's contribution to advancing these technologies.
KAUST researchers have developed a detailed 3D dynamic model using data from the February 2023 Turkiye earthquake to improve earthquake simulations. The model incorporates 3D fault geometry and Earth structure for realistic simulations of ground shaking. It explains complex ground shaking patterns and the impact of supershear ruptures, which can amplify damage far from the epicenter. Why it matters: This research provides a more accurate understanding of earthquake rupture processes, crucial for seismic hazard assessment and infrastructure planning in seismically active regions like the Middle East.
KAUST researchers from statistics and earth science collaborated to improve earthquake source modeling. They developed a statistical ranking tool to classify 2D fields, applicable to geoscience models like temperature or precipitation. The tool helps compare different 2D fields describing the earthquake source process and quantify inter-event variability. Why it matters: This cross-disciplinary approach enhances the reliability of earthquake rupture models, contributing to better hazard assessment and risk management in seismically active regions.
KAUST Ph.D. student Zhaolun Liu won the best student presentation at the 2017 Society of Exploration Geophysicists (SEG) Full-Waveform Inversion (FWI) and Beyond Workshop in Beijing. Liu's presentation was on "3D Wave-Equation Dispersion Inversion of Surface Waves," based on a paper co-authored with Jing Li and Professor Gerard Schuster. The paper describes a new method called wave equation dispersion inversion (WD) for inverting surface waves. Why it matters: This award recognizes KAUST's contributions to geophysics and seismic imaging, highlighting the university's research capabilities and access to high-performance computing.
KAUST's supercomputer Shaheen completed ultra-resolution subsurface mapping simulations for Saudi Aramco, producing a 3D image of subsurface geologic layers at a 7.5-meter resolution. Aramco scientists used integrated GeoDRIVE software to achieve this record resolution at a production scale, improving on prior simulations with tens of meters resolution. Shaheen, located in the KAUST Supercomputing Core Laboratory, is one of the largest CPU-based supercomputers globally, featuring 12,348 Intel Haswell CPUs. Why it matters: This achievement enables more precise resource extraction and geological understanding in the Arabian Peninsula, demonstrating the growing capabilities of regional supercomputing for industrial applications.
KAUST alumnus Hassan Al-Ismail (M.S. '14) leads a team at Saudi Aramco implementing vibrational wave modeling of 2D data. He returned to Saudi Arabia to work for Saudi Aramco after receiving his bachelor's degree and was later sponsored by the company to study at KAUST. Al-Ismail also emphasized the value of his time at KAUST for academic and personal growth. Why it matters: This highlights KAUST's role in developing talent for key industries in Saudi Arabia, particularly in areas relevant to energy and resource management.