Help us shape the first truly useful AI orchestrator for geoscience projects. This short survey (5–7 minutes) will help us understand your team, your workflows, and whether GeoManager AI-Agent is a good fit for your seismic interpretation projects. By answering these questions, you’ll get a chance to join a small group of early adopters, influence our roadmap, and be among the first to try Geoplat’s new AI‑powered experience in real projects.
Geological bodies (reefs, channels, diapirs) form complex reservoirs whose morphology and internal structure determine the volume of reserves and the development strategy. The detection and interpretation of their boundaries is a time-consuming and subjective process that depends on the specialist's experience.
Their inaccurate localization is critical and leads to the following consequences:
Misleading correct drilling with loosing on one well up to $3 mln
Leading to poor oil recovery factor from many wells
Resulting in errors of reserves estimation up to 50%
Transfer learning technology allows you to apply interpretator’s knowledge of the geology. Therefore, the solution is combining ML algorithms and human vision on the data.
From several hours to 2-3 days
1 or 2 parameters only per procedure
- Stacked seismic data of any quality;
- Manual geobody picks on 2–5 sections of the volume
in a standard format for integration into interpretation process
for specific object type by manually marking some of their boundaries
on geobodies distribution across the entire volume of seismic data
Geobodies classification
-
Terrigenous reservoirs- Paleo-channels
- Delta branches
- Underwater channels
- Cut-in valleys
-
Carbonate and biogenic reservoirs- Barrier reefs
- Atolls
- Carbonate platforms
-
Evaporite (salt) structures- Salt pillows
- Salt diapirs
- Salt domes
- Salt ramparts
-
Volcanogenic objects- Underwater volcanic structures
- Lava plateaus and streams
- Tuff bodies
-
Geohazards- Shallow Gas Accumulations
- Karst
- Scours
- Landslide Slip Planes
-
Cryogenic and glacial objectsGlacial valleys
Moraines (glacial-clastic bodies)
Fluvioglacial deposits
by 2 times due to the sedimentation model's detalization
by minimization routine picking geobody boundaries up to 90%
to adjust well trajectories and reduce financial losses