Fault picking software
Two routes to the same fault network: a neural-network wizard that runs a 3D volume from detection through to clustered fault sticks, and hand picking on every section, map and 3D view — in time or in depth, with the discontinuity attributes on screen while you work.
From a seismic cube to fault objects.
The AI Faults Wizard runs a complete cycle in three stages, each one feeding the next automatically. It needs a 3D SEG-Y cube in the project — two-dimensional data is not supported — and executes on CPU or on an NVIDIA GPU. Run the stages one at a time to inspect each result, or press Calculate All and let it work through them; either way the settings can be saved into a project workflow and re-run later.
A trained network analyses the fracture pattern and writes a fault-probability volume. Two models are available — a baseline that takes any window size, and a transformer fixed at 128 — with the analysis window, its overlap and a vertical range that can follow a horizon instead of a fixed time.
Planarity measures how continuous the reflections are; from it come faultness, which highlights the fault centreline, and orientation, which records its strike in map view. A sharp, balanced or smooth preset covers most data, and a custom mode exposes the smoothing and continuity scales.
Sticks are traced along the centrelines, each extending while the fault stays pronounced and its strike stays inside the orientation tolerance. Sticks are then grouped into faults only where they are mutual neighbours — the rule that stops branches from being merged into one fault by mistake.
Set dip, strike and size ranges on a compass before the run and only the faults that pass are ever created; after it, every fault of the run appears as a marker you can point at to read its dip, azimuth and size.
Confine detection to a polygon and a vertical interval — useful for trying parameters on a representative area before committing the whole volume to a run that can take hours.
Faults land in the Data Manager under Time or Depth, meshed as sticks or as surfaces, and are displayed in the 3D view, on the map and on sections — then edited, extended and exported like any hand-picked fault.
The interpreter still owns the structure.
Automatic detection is a starting point, not a verdict. Everything below is the hand work around it — picking where the network is quiet, correcting where it is wrong, and giving the result the geological meaning a probability volume cannot.
Six steps from a raw cube to a fault framework.
A fault is project data, not a drawing.
Every fault sits in the Data Manager with its domain, its sticks, its surface, its type and its colour — which is why the same object can drive a map, a model and an export without being redrawn.
Faults are half of the structural picture.
The other half is the horizons they cut, the wells that date them and the model they are built into. These are the other topics in the g-Space workflow.
Questions, answered.
What does the AI Faults Wizard actually produce?
Can faults still be picked by hand?
What is the difference between sticks and surface mode?
How do picked faults reach the maps and the model?

Run the detection on your own cube.
Point the wizard at a polygon in your survey, compare the presets, and see what the network finds before you commit the whole volume — take g-Space for a trial run, or talk to Geomage about a demo.






