Atlas Deep Geo turns sparse 2D seismic lines into probabilistic 3D volumes — P10, P50, P90 — so you know what the data supports and what remains uncertain.
Every problem we solve is a variant of the same problem: sparse or missing observations in a known geometry, reconstructed with a learned geological prior. The observation type differs. The mask geometry differs. The framework does not.
Residual learning on a classical smooth prior. Horizon flattening. Full-extent slabs. Ensemble uncertainty quantification.
How it works →2D-to-3D reconstruction, infill, obscured-zone imaging, footprint removal. One capability, four contexts.
Explore ORCA →Penobscot. Glacier monitoring. Real datasets, honest validation, published figures.
View studies →RBF interpolation gives one answer. Sparse inversion gives one answer. ORCA gives a distribution of answers — each geologically plausible — with the spread across realizations quantifying the irreducible uncertainty from limited observations. That changes the conversation from "here is our best estimate" to "here is the range of structures consistent with your 2D data."