# Rotary Drill Operators, Oil and Gas

> Set up or operate a variety of drills to remove underground oil and gas, or remove core samples for testing during oil and gas exploration.

- **SOC code:** 47-5012.00
- **Canonical URL:** https://singulariki.com/roles/role-47-5012-00
- **Also known as:** Daylight Driller, Drill Operator, Driller, Tool Pusher, Drilling Rig Operator, Motor Man, Oil Rig Driller, Oil Well Driller
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Train crews, and introduce procedures to make drill work more safe and effective.
- Observe pressure gauge and move throttles and levers to control the speed of rotary tables, and to regulate pressure of tools at bottoms of boreholes.
- Count sections of drill rod to determine depths of boreholes.
- Push levers and brake pedals to control gasoline, diesel, electric, or steam draw works that lower and raise drill pipes and casings in and out of wells.
- Connect sections of drill pipe, using hand tools and powered wrenches and tongs.
- Maintain records of footage drilled, location and nature of strata penetrated, materials and tools used, services rendered, and time required.
- Maintain and adjust machinery to ensure proper performance.
- Start and examine operation of slush pumps to ensure circulation and consistency of drilling fluid or mud in well.
- Locate and recover lost or broken bits, casings, and drill pipes from wells, using special tools.
- Weigh clay, and mix with water and chemicals to make drilling mud.
- Direct rig crews in drilling and other activities, such as setting up rigs and completing or servicing wells.
- Monitor progress of drilling operations, and select and change drill bits according to the nature of strata, using hand tools.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Problem Sensitivity _(ability)_
- Control Precision _(ability)_
- Near Vision _(ability)_
- Mechanical _(knowledge)_
- Mathematics _(knowledge)_
- Arm-Hand Steadiness _(ability)_
- Manual Dexterity _(ability)_
- Multilimb Coordination _(ability)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Information Ordering _(ability)_
- Critical Thinking _(essential_skill)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Instructing _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Writing _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- Python _(hot technology)_
- Salesforce software _(hot technology)_
- SAP software _(hot technology)_
- CAPSHER Technology SureTec
- Drillingsoftware DrillPro
- Drillingsoftware Tubular Database
- Pason WellView Field Solution
- Schlumberger Petrel E&P
- Structure query language SQL

## AI exposure & outlook

- **AI task-overlap index:** 13th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 26th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 8th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 13th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 48th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 0.2% growth (About average); 1.2k annual openings; 13.3k → 13.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $65,010; 13,090 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-47-5012-00_