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2 - OGE - Oil & Gas


OGE 106 - Geostatistics and Reservoirs Modeling

Code Start Date Duration Venue Fees
OGE 106 07 April 2018 5 Days Istanbul $ 3950 Registration Form Link
OGE 106 02 June 2018 5 Days Istanbul $ 3950 Registration Form Link
OGE 106 28 July 2018 5 Days Istanbul $ 3950 Registration Form Link
OGE 106 22 September 2018 5 Days Istanbul $ 3950 Registration Form Link
OGE 106 17 November 2018 5 Days Istanbul $ 3950 Registration Form Link
OGE 106 15 December 2018 5 Days Istanbul $ 3950 Registration Form Link

 

Course Description

This course designed to understanding the fundamental theory and practice of reservoir description and modeling for reservoir management. Participants will learn the fundamental concepts of reservoir description and modeling using geostatistical techniques. This course emphasizes the principles and practice of integrated studies and uncertainty analysis

Course Objectives

  • Learning how to apply reservoir description and modeling to support reservoir management
  • Recognizing the limitations and opportunities of reservoir modeling.
  • Learning the Kriging techniques
  • Understanding the  statistics and probability 

Who Should Attend?

  • Petroleum/ Geophysicists/ Geologists/Reservoir engineers
  • Technical/ reservoir engineers
  • Processing engineers
  • Commercial analysts
  • Decision makers/ investors in oil and gas sector

Course Schedule

Day 1

  • Course Objectives
  • Fundamentals of Reservoir Modeling 
  • Basic Statistical Principles 
  • Probability Principles 

Day 2

  • Data Analysis
  • Quality Control 
  • Preparation 
  • Variogram Modeling 

Day 3

  • Kriging Techniques 
  • Stochastic Simulation 
  • Modeling Case Studies 
  • Overview of Uncertainty Analysis 

Day 4

  • Overview of Integrated Studies
  • Spatial Modeling
  • Structural Modeling
  • Estimation of Properties at Well Locations

Day 5

  • Conditional Simulation
  • Facies/Rock Type Modeling
  • Petrophysical Properties Simulation
  • Ranking of Realizations
  • Construction of Simulator Input Model
  • Future Predictions and Quantification of Uncertainty