Harnessing Generative and Agentic AI to Facilitate Seismic Processing and Imaging

This extended abstract describes the integration of generative AI (GenAI) and agentic AI into seismic processing and imaging workflows, aiming to simplify complex tasks and reduce manual effort. The AI assistant leverages large language models and retrieval-augmented generation, drawing on decades of proprietary geophysics knowledge to provide contextual guidance via an interactive chat interface. Key features include secure enterprise integration, robust governance, and scalable architecture. Initial results show that 75% of users found the assistant improved task efficiency, though challenges remain in reliably interpreting user intent and ensuring context-aware responses. Future directions focus on expanding agentic capabilities for autonomous data management, workflow setup, and peer-reviewed automation, with projected annual efficiency savings in the tens of millions of dollars. The implementation demonstrates significant benefits in time savings, reliability, and user experience, with ongoing development aimed at further automating complex subsurface imaging tasks and redefining human-machine collaboration.