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CMG Training:
CMOST for Conventional and Tight Reservoirs
Location: 
Houston
Cost: 
$1000 USD per person
Course Date: 
Wednesday, 7 August, 2019 - 08:30 to Thursday, 8 August, 2019 - 16:30

Who should attend

This two-day course is for the experienced reservoir simulation engineer or other technical personnel who would like to learn the techniques of Sensitivity Analysis, Assisted History-Matching, Optimization and Uncertainty Analysis. Users should be familiar with the use of BUILDER to create and edit CMG reservoir simulator models (IMEX, GEM or STARS).

About the course

CMOST is CMG’s Sensitivity Analysis, automated History Matching, Optimization, and Uncertainty Assessment software and is designed to work with all three of CMG’s reservoir simulators (i.e. IMEX, GEM & STARS). This course introduces these four tasks from the practical application perspective. The theoretical basis of optimization algorithms is lightly covered with the focus being on the application of the software to real-world problems.

Course Content

  • Introduction to the four components of CMOST:
    • Sensitivity analysis
    • History matching
    • Optimization
    • Uncertainty assessment
  • Introduction to the CMOST Studio, explain how to create the CMOST data files, i.e. master data set, and task file
  • Exercise and tutorial.

For inquiries regarding CMG training courses, please contact us by
Email or Phone at +1.403.531.1300.

Meals and refreshments are included in all course fees
Please Note: In order to register for CMG courses, please click here to login to your online account, or click the icon above
Bogota
Course Date
Tuesday, 15 October, 2019 - 08:30 to Thursday, 17 October, 2019 - 16:30
Houston
Course Date
Wednesday, 10 July, 2019 - 08:30 to Thursday, 11 July, 2019 - 16:30
Wednesday, 7 August, 2019 - 08:30 to Thursday, 8 August, 2019 - 16:30
Thursday, 5 September, 2019 - 08:30 to Friday, 6 September, 2019 - 16:30
Thursday, 3 October, 2019 - 08:30 to Friday, 4 October, 2019 - 16:30
Wednesday, 6 November, 2019 - 08:30 to Thursday, 7 November, 2019 - 16:30