Reservoir Modeling and Data Integration

Course CodeEN00115

Available Dates & Locations

This course is available in multiple locations and online. Choose the most suitable date and delivery method.

Istanbul

Dates

Istanbul

Venue / Hotel

DoubleTree by Hilton Istanbul Esentepe

19 Mayıs Mahallesi, 19 Mayis Street No 2 Sisli, 34360 Istanbul/İstanbul

Hotel Website
Duration
1 Week
Price
€6,825

Course Overview

Reservoir modeling is a critical process in upstream oil and gas operations, enabling accurate representation of subsurface conditions and supporting effective decision-making for field development and production optimization. Integrating geological, geophysical, and engineering data ensures reliable models that enhance forecasting and reservoir management.

This program, designed by Global Horizon Training Center, equips participants with the knowledge and practical skills required to build, analyze, and integrate reservoir models using multidisciplinary data for improved asset performance.

Course Objectives

By the end of this program, participants will be able to:

  • Understand the fundamentals of reservoir modeling and simulation
  • Integrate geological, geophysical, and production data into reservoir models
  • Develop static and dynamic reservoir models
  • Apply data interpretation techniques for model accuracy
  • Perform history matching and forecasting
  • Identify uncertainties and manage modeling risks
  • Optimize reservoir performance using simulation outputs
  • Support field development planning and decision-making

Who Should Attend

This program is designed for:

  • Reservoir Engineers and Petroleum Engineers
  • Geologists and Geophysicists
  • Production and Field Development Engineers
  • Data Analysts in upstream oil and gas
  • Asset Management and Planning Professionals
  • Technical Specialists involved in reservoir studies

Course Outline

  • Overview of reservoir modeling concepts and workflows
  • Types of reservoir models (static vs. dynamic)
  • Geological and petrophysical data fundamentals
  • Data sources and quality assessment
  • Introduction to modeling software and tools