Locate and estimate probable natural gas, oil, or mineral ore deposits or underground water resources, using aerial pho…
Locate and estimate probable natural gas, oil, or mineral ore deposits or underground water resources, using aerial photographs, charts, or research or survey results.
Task automation exposure
Very low exposure
Exposure basis
[v4/median] score 15 (raw 15 | A 15 / B 15 / C 35 | modality: other) While AI and machine learning can process aerial imagery and geological data to identify potential anomalies, the task of locating and estimating deposits requires complex 3D subsurface modeling, integration of diverse physical survey data (seismic, gravity, magnetic), and expert (capable: Geological modeling software (e.g., Petrel, GOCAD) with AI-assisted anomaly detection)
0 capabilities · 1 occupations
Basis
How exposure was assessed
[v4/median] score 15 (raw 15 | A 15 / B 15 / C 35 | modality: other) While AI and machine learning can process aerial imagery and geological data to identify potential anomalies, the task of locating and estimating deposits requires complex 3D subsurface modeling, integration of diverse physical survey data (seismic, gravity, magnetic), and expert (capable: Geological modeling software (e.g., Petrel, GOCAD) with AI-assisted anomaly detection)
How much of this task's output current AI can produce or substantially assist.
Best current model strength on any capability this task requires.
This is an assessment of technical feasibility plus published evidence - not a forecast. Even fully automatable tasks are often not automated, because of cost, verification, liability, regulation or the fact that the task is bundled with other work.
Occupations
Occupations that perform this task (1)
Importance is the O*NET-style weight of this task within each occupation. The same task can be highly exposed but peripheral to one job and core to another.
| Occupation | Industry | Importance | Role | Occupation AI exposure |
|---|---|---|---|---|
| Geoscientists, Except Hydrologists and Geographers | Cross-industry | 4.1/5 | core | 8 |
Evidence
Evidence (0)
No evidence item is mapped to this specific task yet. The exposure figure above rests on the v1 editorial baseline and on the capability assessment, and should be treated as low-confidence. Pages with fewer than 0 evidence items are excluded from sitemaps.