Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Occupation · SOC 19-4043.00
Assist scientists or engineers in the use of electronic, sonic, or nuclear measuring instruments in laboratory, exploration, and production activities to obtain data indicating resources such as metallic ore, minerals, gas, coal, or petroleum. Analyze mud and drill cuttings. Chart pressure, temperature, and other characteristics of wells or bore holes.
Also called: Geological Technician · Geotechnician · Materials Technician · Physical Science Technician · Core Inspector · Environmental Field Services Technician · Environmental Sampling Technician · Geological E-Logger · Geoscience Technician · Soils Technician · Acid Tester · Chalk Tester
Job family: Life, Physical, and Social Science Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-19-4043-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
50th-percentile task overlap — yet about 1,300 openings a year (+1.5% projected, BLS) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 58th | 0.7 | |
| AI assistant applicability (Microsoft) Moderate | 42nd | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.4), and including AI-powered software (γ 0.7). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Compile, log, or record testing or operational data for review and further analysis. | 1.8% | |
| Assemble, maintain, or distribute information for library or record systems. | 0.7% | |
| Test and analyze samples to determine their content and characteristics, using laboratory apparatus or testing equipment. | 0.3% | |
| Create photographic recordings of information, using equipment. | 0.3% | |
| Interview individuals, and research public databases in order to obtain information. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +1.5% by 2034 |
| Projected annual openings | 1,300 |
| Employment 2024 → 2034 | 9,800 → 10,000 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
All 30 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Written Comprehension | 3.9 | |
| Oral Comprehension | 3.8 | |
| Information Ordering | 3.5 | |
| Near Vision | 3.5 | |
| Oral Expression | 3.4 | |
| Written Expression | 3.4 | |
| Inductive Reasoning | 3.4 | |
| Deductive Reasoning | 3.3 | |
| Category Flexibility | 3.3 | |
| Speech Clarity | 3.3 | |
| Flexibility of Closure | 3.1 | |
| Speech Recognition | 3.1 | |
| Problem Sensitivity | 3.0 | |
| Mathematical Reasoning | 3.0 | |
| Perceptual Speed | 3.0 | |
| Selective Attention | 3.0 | |
| Far Vision | 3.0 | |
| Fluency of Ideas | 2.9 | |
| Visual Color Discrimination | 2.9 |
| Reading Comprehension | 3.8 | |
| Critical Thinking | 3.5 | |
| Writing | 3.3 | |
| Monitoring | 3.3 | |
| Active Listening | 3.1 | |
| Speaking | 3.0 | |
| Mathematics | 2.8 | |
| Active Learning | 2.8 |
| Computers and Electronics | 3.5 | |
| Engineering and Technology | 3.5 | |
| Mathematics | 3.5 | |
| English Language | 3.5 | |
| Chemistry | 3.2 | |
| Physics | 3.1 | |
| Geography | 3.1 |
| Time Management | 3.3 | |
| Complex Problem Solving | 3.1 | |
| Judgment and Decision Making | 3.1 | |
| Coordination | 3.0 | |
| Operations Monitoring | 3.0 | |
| Social Perceptiveness | 2.9 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Engineering/Engineering-Related Technologies/Technicians , Physical Sciences , Science Technologies/Technicians . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
The interests and personal qualities O*NET associates with people who do this work.
| Physical Science | 5.8 | |
| Engineering | 3.8 | |
| Mechanics/Electronics | 3.6 | |
| Mathematics/Statistics | 3.6 | |
| Nature/Outdoors | 2.7 | |
| Physical/Manual Labor | 2.5 | |
| Information Technology | 2.3 | |
| Office Work | 2.0 | |
| Transportation/Machine Operation | 1.8 |
| Realistic | 5.6 | |
| Conventional | 5.3 | |
| Investigative | 5.2 |
| Attention to Detail | 2.6 | |
| Dependability | 2.1 | |
| Intellectual Curiosity | 1.9 | |
| Integrity | 1.7 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $32,830 |
| 25th percentile | $39,200 |
| Median (50th) | $48,390 |
| 75th percentile | $64,470 |
| 90th percentile | $92,210 |
| People employed | 9,710 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Professional, Scientific, and Technical Services · Sector | 5,310 | $48,330 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 3,240 | $45,480 |
| Engineering Services · National industry | 2,830 | $50,960 |
| Testing Laboratories and Services · National industry | 740 | $43,090 |
| Manufacturing · Sector | 280 | $57,880 |
| Educational Services · Sector | 180 | $53,290 |
| Transportation and Warehousing · Sector | 130 | $45,950 |
| Management of Companies and Enterprises · Sector | 120 | $95,470 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 110 | $63,840 |
| Utilities · Sector | 60 | $83,520 |
| Real Estate and Rental and Leasing · Sector | — | $76,620 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 89.71× | 3,240 |
| Testing Laboratories and Services · National industry | 68.96× | 740 |
| Engineering Services · National industry | 38.87× | 2,830 |
| Professional, Scientific, and Technical Services · Sector | 7.83× | 5,310 |
| Management of Companies and Enterprises · Sector | 0.68× | 120 |
| Manufacturing · Sector | 0.35× | 280 |
| Transportation and Warehousing · Sector | 0.28× | 130 |
| Educational Services · Sector | 0.21× | 180 |
Part of the Energy & Natural Resources and Public Service & Safety career clusters.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Geological Technicians, Except Hydrologic Technicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
See where this work sits in the bigger picture.
Geological Technicians, Except Hydrologic Technicians show 50th-percentile AI task overlap — and about 1,300 annual U.S. openings
Geological Technicians, Except Hydrologic Technicians show 50th-percentile AI task overlap — and about 1,300 annual U.S. openings • Geological Technicians, Except Hydrologic Technicians rank in the 50th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 1,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+1.5%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $48,390, across about 9,710 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Geological Technicians, Except Hydrologic Technicians". https://singulariki.com/roles/role-19-4043-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
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Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Geological Technicians, Except Hydrologic Technicians." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/roles/role-19-4043-00
Singulariki. (2026). Geological Technicians, Except Hydrologic Technicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-19-4043-00
@misc{singulariki-role-19-4043-00,
title = {Geological Technicians, Except Hydrologic Technicians},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-19-4043-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.