Until recently, we haven’t trusted automated methods for estimating velocity models for depth imaging in complex-structure land environments. We have relied exclusively on human learning to build interpretive, geologically constrained velocity models. Preliminary results from Greg’s research show impressive value in machine learning to optimize velocity models for seismic imaging
