Petroleum Engineers
In short: today's best AI models could do about 20% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 66% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 33% of the time, stays with people.
Devise methods to improve oil and gas extraction and production and determine the need for new or modified tool designs. Oversee drilling and offer technical advice.
18,060 people do this job in the US. $144,910 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on8 h
- A person checks AI's work0 h
- Desk work AI can't do yet19 h
- Stays with people13 h
Petroleum Engineers, now: of a 40-hour week, AI could take on 8 hours, 0 hours become checking its work, 19 hours are desk work it can't do yet, and 13 hours stay with people.
The largest pieces: Analyze data to recommend placement of wells and supplementary processes to enhance production (about 1 h); Monitor production rates, and plan rework processes to improve production (under an hour); Maintain records of drilling and production operations (under an hour).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 67%
- 22%
- 11%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 3%. Today's estimate: 20%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 23 tasks showed up. Within each of Anthropic's methods, never across a change: 0.002% to 0.006% (released February and March 2025).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.002% | 699 of 708 | 1 of 23 |
| Released March 2025 | 0.006% | 562 of 703 | 2 of 23 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 23 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 23 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 23 |
| April 2026 (released June 2026) | none | n/a | 0 of 23 |
| May 2026 (released June 2026) | none | n/a | 0 of 23 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 23 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Direct and monitor the completion and evaluation of wells, well testing, or well surveys.Done more than yearly by most who do it. | 11% | 1.7 work days3.3 h to 4.2 work days | Stays with people | |
| Simulate reservoir performance for different recovery techniques, using computer models.Done more than yearly by most who do it. | 11% | 3.3 work days6.7 h to 1.7 work weeks | 10%Half by Sep 2027 | |
| Design and implement environmental controls on oil and gas operations.Done more than yearly by most who do it. | 11% | 3.3 work days6.7 h to 1.7 work weeks | 10%Half by Sep 2027 | |
| Develop plans for oil and gas field drilling, and for product recovery and treatment.Done more than monthly by most who do it. | 11% | 3.3 work days6.7 h to 1.7 work weeks | 10%Half by Sep 2027 | |
| Specify and supervise well modification and stimulation programs to maximize oil and gas recovery.Done more than weekly by most who do it. | 11% | 1.7 work days3.3 h to 4.2 work days | Stays with people | |
| Analyze data to recommend placement of wells and supplementary processes to enhance production.Done more than monthly by most who do it. | 9% | 1.7 work days3.3 h to 4.2 work days | 31%Half by Mar 2027 | |
| Evaluate findings to develop, design, or test equipment or processes.Done more than monthly by most who do it. | 5% | 1.7 work days3.3 h to 4.2 work days | 31%Half by Mar 2027 | |
| Conduct engineering research experiments to improve or modify mining and oil machinery and operations.Done more than yearly by most who do it. | 5% | 4.2 work days6.7 h to 2.5 work weeks | Stays with people | |
| Assess costs and estimate the production capabilities and economic value of oil and gas wells, to evaluate the economic viability of potential drilling sites.Done more than yearly by most who do it. | 5% | 1.7 work days3.3 h to 4.2 work days | 31%Half by Mar 2027 | |
| Coordinate the installation, maintenance, and operation of mining and oil field equipment.Done more than yearly by most who do it. | 3% | 6.7 h1.7 h to 2.5 work days | 55%Half by now | |
| Supervise the removal of drilling equipment, the removal of any waste, and the safe return of land to structural stability when wells or pockets are exhausted.Done more than yearly by most who do it. | 3% | 1.7 work days3.3 h to 4.2 work days | Stays with people | |
| Design or modify mining and oil field machinery and tools, applying engineering principles.Done more than monthly by most who do it. | 2% | 3.3 work days6.7 h to 1.7 work weeks | 10%Half by Sep 2027 |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Mining and Geological Engineers, Including Mining Safety Engineers10% now, 64% by 2028
- Chemical Engineers19% now, 70% by 2028
- Geothermal Production Managers43% now, 74% by 2028
- Water/Wastewater Engineers11% now, 75% by 2028
- Industrial Engineers60% now, 86% by 2028
- Mechanical Engineers23% now, 70% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Petroleum Engineers is within reach of AI now?
- An estimated 20% of the working time is within reach of AI models now and 66% by the end of 2028, on METR's long-run pace at four in five (52% to 67% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Petroleum Engineers come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Analyze data to recommend placement of wells and supplementary processes to enhance production (31% of the task's time now, 100% by the end of 2028); Monitor production rates, and plan rework processes to improve production (97% of the task's time now); and Maintain records of drilling and production operations (99% of the task's time now).
- Which tasks of Petroleum Engineers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Direct and monitor the completion and evaluation of wells, well testing, or well surveys; Specify and supervise well modification and stimulation programs to maximize oil and gas recovery; and Conduct engineering research experiments to improve or modify mining and oil machinery and operations. Together such tasks are about 33% of the working time.
- Do people already use AI for the work of Petroleum Engineers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Petroleum Engineers?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 23 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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