Master of Engineering in Petroleum Engineering

The Master of Engineering degree in the Department of Petroleum Engineering is a non-thesis-based degree designed to strengthen technical expertise and broaden career opportunities.

This program prepares graduates for leadership roles in the field of their choice. Recognized worldwide “Aggie Petroleum Engineers” are on the forefront of the petroleum industry.

The Master of Engineering (MEng) program offers instruction on topics including:

  • Conventional and Unconventional Oil and Gas Reservoirs — Development and assessment of conventional reservoirs and unconventional resource plays, gas reservoir engineering and management, reservoir fluids (PVT/EOS) characterization and applications in reservoir engineering, petroleum economics and project evaluation for conventional and unconventional developments, natural gas hydrates, diagnosis and analysis/modeling of well performance and integrated risk/uncertainty evaluation and decision analysis supporting development planning.
  • Distributed Acoustics, Temperature and Fiber Optics (Strain) Sensing and Interpretation — Distributed acoustic/temperature/strain sensing (DAS/DTS/DSS), fiber-optic and downhole surveillance, production logging and monitoring, interpretation for flow profiling and well/reservoir diagnostics, and integration of sensing data into reservoir management and production optimization workflows.
  • Reservoir Characterization and Management — Integrated reservoir characterization and reservoir management using reservoir properties, fluids, geomechanics, and production data; closed-loop reservoir management, production optimization and control, history matching/data assimilation, inverse modeling workflows and multi-scale data integration for decision support.
  • Analytical, Numerical and Data-Driven Modeling — Analytical, semi-analytical, and hybrid-analytical numerical methods for modeling/optimization/prediction, numerical simulation and advanced computing workflows, streamline simulation, inverse modeling and multi-scale data integration, physics-based and data-driven multi-physics modeling in porous media for reservoir performance prediction, forecasting, and uncertainty assessment/quantification.
  • Coupled Computing Processes — Coupled flow, thermal, geomechanical, geochemical and geophysical modeling and simulation; multi-scale coupled computing for reservoir–wellbore systems; integration of coupled flow models with field measurements for improved prediction, optimization and operational decision-making.
  • Enhanced and Improved Oil Recovery (EOR/IOR) — Enhanced oil recovery (EOR) and improved oil recovery (IOR) methods, chemical and gas injection approaches, thermal and heavy oil recovery methods, screening/evaluation and optimization of EOR/IOR projects, and integration of reservoir/fluid/rock and operational constraints to maximize hydrocarbon recovery.
  • Artificial Lift, Flow Assurance and Production Optimization — Artificial lift technologies and design/optimization, flow assurance challenges and mitigation, production optimization and control (including closed-loop strategies), production monitoring/surveillance and troubleshooting, and well performance diagnostics to sustain efficient/effective hydrocarbon flow and optimal operational metrics.
  • Drilling, Well Completions and Stimulation — Physics-based drilling performance, deepwater drilling, well control, well completions design and implementation, well stimulation (hydraulic fracturing, acidizing, profile modification), well abandonment practices and well integrity considerations, and drilling/completions designs informed by wellbore stability and geomechanical constraints.
  • Carbon Capture, Utilization and Storage (CCUS) and Energy Transition — CCUS subsurface engineering and storage performance/risk considerations, energy transition and decarbonization strategies in the subsurface, geothermal resource development, subsurface hydrogen (H₂) storage, natural hydrogen and natural nitrogen concepts (as applicable to subsurface engineering) and subsurface aspects of critical minerals.
  • Petrophysics and Multiphase Flow in Porous Media — Reservoir petrophysics (laboratory methods and formation evaluation), multiphase flow in porous media (theory and applications), rock/fluid characterization including multiphase reservoir fluid applications in reservoir engineering, and combinations of physics-based and data-driven modeling approaches relevant to multiphase and multiphysics transport.
  • Machine Learning and Data Analytics — Machine learning and data analytics for petroleum engineering workflows, sensor validation and data quality control, reservoir modeling and hybrid physics-informed ML approaches, inverse modeling and data integration, production forecasting and predictive analytics, and data-driven decision-making for operations and development planning.
  • Surface Facilities, Waste Management and Leak Detection — Surface facilities related to oil and gas production, produced and waste water management, oilfield leak detection for facilities and pipelines, monitoring approaches supporting infrastructure integrity, and environmental impact mitigation and operational risk reduction for surface systems.
  • Geomechanics and Wellbore Stability — Reservoir geomechanics (theoretical, experimental, and applied methods), stress/strain analysis and rock behavior characterization, fracture mechanics (including stimulation-related geomechanics), wellbore stability analysis and geomechanics-informed well design, and coupled flow–geomechanics considerations across depletion, stimulation and field development applications.

Students are mentored by internationally acclaimed faculty, including National Academy of Engineering members and numerous Society of Petroleum Engineers (SPE) award recipients.

This program is also approved for delivery via asynchronous distance education technology, providing flexibility for students, including working professionals.