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.
The UAE's Ministry of Energy and Infrastructure (MoEI) and the Technology Innovation Institute (TII) have partnered to create 3D maps of the UAE's mineral and renewable resources. TII's Directed Energy Research Center (DERC) will support MoEI in this effort, contributing its expertise to identify resources like geothermal energy and analyze geological data. The collaboration aims to support the UAE's Net Zero 2050 Strategy by enabling the exploration and utilization of undiscovered renewable and mineral resources. Why it matters: This initiative leverages local expertise to map domestic resources, aligning technological advancement with sustainability goals for the UAE.
Researchers from the Directed Energy Research Center (DERC) will present research papers at the 17th Workshop of the International Lithosphere Program Task Force on Sedimentary Basins in Abu Dhabi. Dr. Meixia Geng's study identifies potential geothermal exploration sites in the UAE based on Curie isotherm depths. Dr. Felix Vega's research demonstrates drone-borne synthetic aperture radar (SAR) for subsurface mapping of underground cavities. Why it matters: These studies showcase the UAE's commitment to sustainable development through geothermal energy exploration and advanced subsurface imaging techniques.
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.
This paper addresses exploration in reinforcement learning (RL) in unknown environments with sparse rewards, focusing on maximum entropy exploration. It introduces a game-theoretic algorithm for visitation entropy maximization with improved sample complexity of O(H^3S^2A/ε^2). For trajectory entropy, the paper presents an algorithm with O(poly(S, A, H)/ε) complexity, showing the statistical advantage of regularized MDPs for exploration. Why it matters: The research offers new techniques to reduce the sample complexity of RL, potentially enhancing the efficiency of AI agents in complex environments.
KAUST hosted the KAUST Research Conference: Advances in Well Construction with Focus on Near-Wellbore Physics and Chemistry from November 7 to 9. The conference was co-chaired by Eric van Oort, a professor at UT Austin, and Tadeusz Patzek, director of the University’s Upstream Petroleum Engineering Research Center. Attendees included professors from the University of Queensland and UT Austin, and directors from GenesisRTS and Labyrinth Consulting Services, Inc. Why it matters: The conference facilitates international collaboration on advancements in petroleum engineering and well construction technologies, which are strategically important for Saudi Arabia.