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 researchers collaborated on a study in Iceland that found a correlation between changes in groundwater composition and earthquakes greater than magnitude 5. The study, published in Nature Geoscience, observed variations in dissolved element concentrations and stable isotopes prior to seismic events in 2012 and 2013. Earthquake prediction remains a challenge with differing views among scientists about its feasibility. Why it matters: Understanding earthquake precursors could lead to improved risk mitigation strategies for urban infrastructure in seismically active regions across the Middle East.
Geophysicists at KAUST are investigating the "doublet" earthquake phenomenon in Turkey, where two strong earthquakes of magnitude 7.8 and 7.7 occurred within nine hours of each other on separate faults. Researchers from the Crustal Deformation and InSAR Group and the Computational Earthquake Seismology research group are using satellite and seismic data to examine the earthquake rupture process. The National Center for Earthquake and Volcano monitoring (NCEV) of the Saudi Geological Survey contributes seismic recordings to the KAUST teams. Why it matters: Understanding such earthquake doublets is crucial for improving seismic hazard assessment and risk mitigation in the region and globally.
KAUST alumnus Jagdish Chandra Vyas (Ph.D. '17) received a Student Presentation Award at the Seismological Society of America (SSA) Annual Meeting for his poster "Mach Wave Coherence in the Presence of Source and Medium Heterogeneity." Vyas's Ph.D. research at KAUST, under the direction of Professor Martin Mai, focused on analyzing the effects of rupture complexity and heterogeneities in Earth structure on near-source ground motions. He is currently a postdoctoral scholar at the University of Canterbury, New Zealand. Why it matters: This award recognizes the high-caliber research being conducted at KAUST and its impact on the field of seismology.
KAUST held the Imaging and Active Tectonics of the Red Sea Region workshop, gathering over 20 international and 30 local researchers. The workshop aimed to improve understanding of seismicity, volcanism, and Earth structure in Saudi Arabia and the Red Sea region. Participants came from countries surrounding the Red Sea, as well as the US, UK, France, Brazil, and South Korea. Why it matters: The event fosters international collaboration and data exchange to better monitor and model seismic and volcanic activity in a geologically active region.
KAUST alumnus Jagdish Chandra Vyas (Ph.D. '17) received a Student Presentation Award at the 2017 Seismological Society of America Annual Meeting for his poster "Mach Wave Coherence in the Presence of Source and Medium Heterogeneity." Vyas's Ph.D. research at KAUST, under Professor Martin Mai, focused on the effects of rupture complexity and heterogeneities in Earth structure on ground motions. Currently a postdoctoral scholar at the University of Canterbury, New Zealand, Vyas credits KAUST's academic environment and facilities for nurturing his research and scientific growth. Why it matters: This award recognizes the high-caliber research conducted at KAUST and highlights the university's contribution to the field of seismology.
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. 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.