First EAGE Workshop on the Role of Artificial Intelligence in Full Waveform Inversion
The First EAGE Workshop on the Role of Artificial Intelligence in Full Waveform Inversion likely aimed to explore the node of two critical areas in geophysics: Full Waveform Inversion (FWI) and Artificial Intelligence (AI). FWI is a sophisticated technique used to create detailed images of subsurface structures by comparing observed seismic waveforms with simulated ones. AI, on the other hand, offers powerful tools for optimizing complex processes, handling vast datasets, and enhancing the accuracy of predictive models.
This workshop likely provided a platform for researchers, practitioners, and industry professionals to discuss how AI can be leveraged to improve FWI algorithms and workflows. Topics of discussion might have included:
Introduction to Full Waveform Inversion (FWI): An overview of FWI principles, methodologies, and applications in geophysics. Current Challenges in FWI: Discussion on the limitations and challenges faced in traditional FWI approaches, such as computational complexity and sensitivity to initial models.
Integration of AI Techniques: Exploration of how AI techniques, including machine learning and deep learning, can enhance FWI by improving computational efficiency, regularization, and inversion stability. Case Studies and Applications: Presentation of real-world examples and case studies showcasing the successful integration of AI in FWI for subsurface imaging and exploration. Future Directions and Opportunities: Examination of emerging trends, research directions, and opportunities for further advancements in AI-driven FWI methodologies. Participants likely had the opportunity to engage in discussions, share their experiences, present research findings, and network with peers and experts in the field.
Overall, this workshop likely served as a valuable forum for advancing understanding and collaboration at the intersection of AI and FWI within the geophysics.