Reduced-Order Modeling and Inversion for Large-Scale Problems of Geophysical Exploration

Explore reduced-order modeling and inversion techniques for large-scale geophysical exploration problems in this comprehensive lecture. Delve into model-driven and data-driven reduced-order models (ROMs) developed for forward modeling and inverse problems in electromagnetic and seismic methods. Learn how these approaches enable real-time solutions and optimization-free inversion algorithms. Examine numerical examples demonstrating the advantages of these techniques over state-of-the-art algorithms. Gain insights from speaker Mikhail Zaslavsky of Schlumberger Doll Research on addressing challenges in geophysical exploration through innovative modeling approaches.

Introduction
Announcements
Contact information
Presentation
Formulation
Examples
Multiinput
Challenges
Goals
General Overview
Model Problem
Model Driven Reduce
Properties
Data Driven
Transfer Function
Summary
Takeaway
Model PD
Acoustic Imaging
Data to Burn