Shuzhen Ye is an AI/ML Product Owner and Developer at Shell in Houston, with over six years of experience building and deploying practical, high-impact artificial intelligence and machine learning solutions in seismic processing and imaging. His work focuses on supporting oil & gas exploration and reservoir development through scalable, efficient AI applications. Shuzhen has a strong track record of delivering AI products within modest budgets and accelerated timelines, successfully deploying more than ten AI solutions across 100+ seismic projects, achieving 4–5× reductions in turnaround time.
Shuzhen holds a Ph.D. in Physics from Rice University and began his industry career as a staff seismic imager at CGG (now Viridien). He later joined Shell as a research petrophysicist, where he developed fiber-optic technologies for strain detection in oil and gas wells. In this session, he explores how AI is transforming seismic workflows, highlighting the growing role of hybrid physics and AI-driven approaches in improving quality control, parameterization, and processing efficiency. The discussion will focus on balancing model-driven and data-driven AI, while delivering measurable business value through faster, more reliable, and scalable seismic solutions in upstream operations.
Key Topics:
- Emerging trends in AI for seismic workflows and hybrid physics-AI approaches
- Balancing model-driven and data-driven AI for scalable and reliable implementation
- Enhancing quality control and parameterization using AI in seismic processing
- Driving speed, efficiency, and business value through AI-enabled seismic solutions
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