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.
U.S. Workers
18,970
Median Salary
$141,280
10-Year Growth
+1.3%
Annual Openings
1,200
Typical entry: Bachelor's degree
23 of 23 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Assess costs and estimate the production capabilities and economic value of oil and gas wells, to evaluate the economic viability of potential drilling sites.
AI: Fully automatable - Given available reservoir models and financial data, AI can reliably estimate production, costs, and economic viability end-to-end for many wells.
Assist engineering and other personnel to solve operating problems.
AI: Fully automatable - Providing diagnostics, root-cause analyses, and recommended fixes to help engineers solve operating problems is well within 2025 AI capabilities and can be delivered end-to-end as actionable assistance.
Maintain records of drilling and production operations.
AI: Fully automatable - Maintaining records of drilling and production operations is a routine data-ingestion, validation, and reporting task that AI systems can fully automate reliably by 2025.
Write technical reports for engineering and management personnel.
AI: Fully automatable - AI can generate complete technical reports, combining data analysis, visualizations, and narrative tailored to engineering and management audiences, often producing publication-ready drafts.
Simulate reservoir performance for different recovery techniques, using computer models.
AI: Fully automatable - Reservoir simulation is primarily computational and by 2025 AI-enhanced simulators and surrogate models can run and evaluate recovery scenarios end-to-end given appropriate input data.
Develop plans for oil and gas field drilling, and for product recovery and treatment.
AI: Partial - AI can generate detailed drilling and recovery plans using models and best practices, but final planning, permitting, and field-specific adaptations require human engineers and on-site decision-making.
Analyze data to recommend placement of wells and supplementary processes to enhance production.
AI: Partial - By 2025 AI can ingest seismic, log, and production data and propose optimal well locations and supplementary processes, but final placement decisions require human domain validation, regulatory sign-off, and field confirmation.
Direct and monitor the completion and evaluation of wells, well testing, or well surveys.
AI: Partial - AI can monitor sensor data, analyze tests, and recommend actions, but directing on-site completion and overseeing physical well operations still require human supervisors and accountable decision-makers.
Monitor production rates, and plan rework processes to improve production.
AI: Partial - AI can continuously monitor rates and generate rework plans and prioritized interventions, yet implementation and nuanced engineering judgments for rework still need human oversight and on-site assessments.
Interpret drilling and testing information for personnel.
AI: Partial - AI models can interpret drilling and test data and produce clear explanations for personnel, but they may miss contextual, site-specific subtleties that experienced engineers must confirm.
Specify and supervise well modification and stimulation programs to maximize oil and gas recovery.
AI: Partial - AI can design candidate well modification and stimulation programs using reservoir models and optimization, but specifying and legally supervising operations requires licensed engineers and on-site management.
Confer with scientific, engineering, and technical personnel to resolve design, research, and testing problems.
AI: Partial - AI can participate in technical discussions, synthesize options, and propose solutions, but resolving complex design/research/testing problems typically requires human negotiation, responsibility, and cross-disciplinary judgment.
Coordinate the installation, maintenance, and operation of mining and oil field equipment.
AI: Partial - AI can plan, optimize, and coordinate schedules, supply chains, and maintenance tasks, but physical installation, safety oversight, and operational decisions on-site require human supervisors.
Design and implement environmental controls on oil and gas operations.
AI: Partial - AI can model environmental impacts and recommend control designs, but implementation, site-specific deployment and regulatory compliance require human-led actions.
Coordinate activities of workers engaged in research, planning, and development.
AI: Partial - AI can automate scheduling, task assignment and information flow to coordinate activities, but cannot fully replace human leadership, real-time judgement and interpersonal management.
Assign work to staff to obtain maximum utilization of personnel.
AI: Partial - AI can optimize assignments and recommend staffing plans based on skills and availability, but final assignment decisions involve human managerial judgment, personnel dynamics, and legal/HR considerations.
Take samples to assess the amount and quality of oil, the depth at which resources lie, and the equipment needed to properly extract them.
AI: Partial - AI can plan sampling strategies and analyze laboratory results, but physically collecting samples in varied field or downhole conditions still requires humans or specialized robotics not universally available.
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.
AI: Partial - AI can generate decommissioning plans, monitor operations and flag risks, but on-site supervision, waste handling and legal sign-off for restoration need human oversight and contractors.
Evaluate findings to develop, design, or test equipment or processes.
AI: Partial - AI can analyze findings, run design optimizations and propose tests, but cannot take full responsibility or perform hands-on validation and sign-off without human oversight.
Inspect oil and gas wells to determine that installations are completed.
AI: Partial - AI-powered drones and sensor analytics can perform much of the inspection work, yet final acceptance, complex checks and regulatory certification typically still require human inspectors.
Conduct engineering research experiments to improve or modify mining and oil machinery and operations.
AI: Partial - AI can design experiments, analyze large datasets and suggest improvements, but conducting physical experiments and iterative prototyping depends on laboratory and field work by humans.
Design or modify mining and oil field machinery and tools, applying engineering principles.
AI: Partial - Generative design and simulation enable AI to propose and optimize machinery, but manufacturability, prototyping, testing and safety certification still require human engineers.
Test machinery and equipment to ensure that it is safe and conforms to performance specifications.
AI: Partial - AI can automate many test procedures and analyze sensor outputs to detect nonconformance, but hands-on testing, safety-critical judgments and legal certification continue to require human involvement.