Practical Oil & Gas training
Courses delivered by a team of upstream & downstream petroleum engineers.
Drilling Engineering & Workover Operations
From drilling and intervention planning to rig-site execution — safe, efficient drilling and workovers that restore production and protect well integrity.
Drill Bits Selection & Optimization
Select, run, and evaluate drill bits to maximize rate of penetration and bit life across different formations.
- Bit types and IADC dull/classification coding
- Bit selection vs. formation and drilling parameters
- Dull grading, bit records, and performance analysis
- Choose the right bit for a given hole section
- Read dull grades and adjust drilling parameters
Workover Operations
Plan and execute common workover activities including completion change, fishing, remedial cement, and stimulation — with well control and troubleshooting awareness.
- Workover objectives, well barriers, rig-up, rig down and various workover rig systems
- completion change, fishing, remedial cement, and stimulation operations
- Well control on live wells
- Plan and execute common workover activities safely
- Apply well-control basics and avoid integrity risks
Production & Facilities Engineering
Covering artificial lift — ESP, gas lift, sucker-rod and jet pumps — nodal analysis, and surface facilities like tanks and separators across the full production system.
Well Performance & Production Analysis
Understand and optimize the full production system using nodal analysis and real field data.
- Inflow and outflow performance fundamentals
- Nodal analysis on real well data
- Identifying and removing production bottlenecks
- Build a nodal model and find the operating point
- Diagnose underperforming wells systematically
Electrical submersible pump (ESP)
Design, select, and optimize ESP systems across a wide range of well conditions and operational challenges.
- ESP system components and operating envelope
- Sizing and selection for variable well conditions
- Failure modes, run-life, and optimization
- Size and select an ESP for a given well
- Spot conditions that shorten ESP run-life
Reservoir Engineering
From rock and fluid properties to drive mechanisms, material balance, and simulation — practical reservoir engineering for forecasting and field development.
Reservoir Engineering Fundamentals
Core reservoir engineering — rock and fluid properties, drive mechanisms, hydrocarbon in place estimate and decline curve analysis.
- Rock and fluid (PVT) properties
- Reservoir drive mechanisms
- Material balance and decline curve analysis
- Identify the drive mechanism and expected recovery
- Apply material-balance basics to a defined reservoir
Geology & Geophysics
From rock and depositional setting to seismic interpretation connecting subsurface geology to reservoir behavior and engineering decisions.
Seismic Interpretation
Interpret seismic data and integrate it to build and refine subsurface models.
- Seismic acquisition and processing basics
- Structure picking e.g., faults, folds and well ties.
- Integrating seismic with well and geologic data
- Interpret a seismic section with confidence
- Combine seismic and well data into a model
Refinery & Petrochemical Engineering
Downstream from crude to product and process fundamentals, conversion units, and petrochemical plant operations for safe, optimized facilities.
Petrochemical Processes
Major petrochemical routes and the operating discipline that keeps plants safe, reliable, and optimized.
- Olefins and aromatics production routes
- Polymer fundamentals and product chains
- Plant safety, reliability, and optimization
- Outline the major petrochemical process routes
- Apply basic optimization and safety principles
Data Science, ML & AI in Petroleum Engineering
Convert field data into reliable engineering decisions — practical AI grounded in petroleum physics and real workflows.
Machine Learning in Petroleum Engineering
Build, validate, and harness ML models for petroleum engineering applications.
- Identifying a gap for ML applications in petroleum engineering
- Data collection, preprocessing, model building and validation
- Model deployment and adoption in a company workflow
- Build and validate an ML model on field data
- Evaluate results and avoid common pitfalls
Train your team
Every course can be delivered as a compact program or an expanded workshop, tailored to your team's level and field requirements.
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