This webinar presents an end-to-end AI workflow for paleochannel interpretation — from seismic volumes to channel boundaries ready for integration into digital geological models. The workflow is built around a flexible combination of pre-trained AI models and user-driven adaptation. Instead of relying on region-specific training, the models are pre-trained on large amount of synthetic data, capturing a wide range of subsurface patterns and seismic responses.

This approach enables immediate application to new datasets, with the option to refine results through user input when required. Interpretation is not fixed: the workflow allows adjustment, iteration, and integration of expert knowledge through annotations and transfer learning.

The session focuses on how this hybrid approach supports:

• Rapid detection of paleochannels across seismic volumes
• Flexible configuration of interpretation workflow;
• Incorporation of user expertise into model predictions;
• Extraction of channel boundaries for geological modeling.

The result is a controllable and transparent interpretation process, where AI operates as part of the workflow rather than as a black-box solution.