This practical one-week course on Petroleum Data Collection is designed to cover fundamentals, techniques, and practical applications for professionals who are new to the field or those needing a concise refresher course. Each day pairs theory with hands-on exercises and short assessments to reinforce learning.

Learning Objectives

At the end of this training session, participants will be able to

• Identify key types of petroleum data (geological, geophysical, drilling, production, reservoir).
• Apply standard techniques for collecting seismic, logging, drilling, and production data.
• Evaluate data quality and implement validation methods to minimize errors.
• Use petroleum data standards (PPDM, WITSML, PRODML) for effective data management.
• Analyze petroleum datasets using basic analytics and visualization tools.
• Integrate data into reservoir models and field development planning.
• Demonstrate practical skills through hands-on exercises and group projects.

Course Contents

Day One:       Introduction to Petroleum Data

• Morning (9:00–12:00)
  • Course overview & objectives
  • Types of petroleum data (geological, geophysical, drilling, production, reservoir)
  • Importance of accurate data collection
• Afternoon (1:30–4:30)
  • Data lifecycle: acquisition → validation → storage → analysis
  • Case study: data-driven exploration success

Day Two:      Geological & Geophysical Data Collection

• Morning
  • Seismic data collection (2D, 3D, 4D surveys)
  • Well logging techniques (wireline, LWD/MWD)
• Afternoon
  • Core sampling and laboratory analysis
  • Data quality assurance and error minimization

Day Three:   Drilling & Production Data

• Morning
  • Drilling parameters: rate of penetration, mud logging, pressure data
  • Real-time drilling data acquisition systems
• Afternoon
  • Production data: flow rates, well tests, choke sizes
  • SCADA, sensors, and IoT applications in oilfields

Day Four:     Reservoir & Field Data

• Morning
  • Reservoir pressure and temperature measurements
  • Formation testing and fluid sampling
• Afternoon
  • Reservoir simulation input data requirements
  • Field development planning and reserves evaluation

Day Five:      Data Management Systems

• Morning
  • Petroleum data standards (PPDM, WITSML, PRODML)
  • Database design for petroleum data
• Afternoon
  • Cloud-based solutions and digital oilfield concepts
  • Cybersecurity and data governance

Day Six:        Petroleum Data Analytics

• Morning
  • Introduction to AI/ML in petroleum data analytics
  • Predictive modeling for reservoir performance
• Afternoon
  • Data visualization tools (Tableau, Power BI, Spotfire)
  • Case study: production optimization using analytics

Day Seven:  Practical Workshop & Case Studies

• Morning
  • Hands-on exercises with petroleum datasets
  • Building a simple reservoir model
• Afternoon
  • Group project: analyze drilling & production data for optimization strategies
  • Wrap-up: future of petroleum data collection and analytics

Course Booking

Please use the “book now” or “inquire” buttons on this page to either book your space or make further enquiries.