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The Reservoir #Static #Modeling in #Petrel Course is an in-depth program designed to provide participants with the knowledge and skills necessary to create accurate and reliable static models of underground reservoirs using the industry-standard Petrel software. Through a combination of theoretical lectures, practical exercises, and hands-on projects, participants will gain a comprehensive understanding of reservoir static modeling principles, techniques, and best practices.

Course Objectives:

Understand the role and importance of reservoir static modeling in reservoir characterization.

Gain proficiency in using the Petrel software, including navigating the interface, and utilizing relevant modules and functionalities.

Learn how to construct realistic reservoir models by integrating geological, geophysical, and engineering data, and applying grid construction and property modeling techniques.

Course Outline:

List of Required Dataset

Structural Framework Construction

Fault Modeling (Pillar Gridding)

Horizon Modeling

Grid Construction: Techniques for creating structured and unstructured grids in Petrel.

Property Modeling: Estimating and assigning petrophysical properties to reservoir models.

Who Should Attend:

Reservoir Engineers involved in reservoir characterization.

Geoscientists, including geologists and geophysicists, working with subsurface data and contributing to reservoir modeling.

Petroleum Engineers engaged in reservoir simulation and field development planning.

Students pursuing degrees or conducting research in reservoir engineering, geology, or related disciplines.

Prerequisites:

Basic knowledge of reservoir engineering and geology concepts is recommended.

Familiarity with Petrel software is beneficial, but not mandatory.

By the end of this course, participants will be equipped with the skills and knowledge to confidently create, analyze, and validate reservoir static models in Petrel. They will be well-prepared to contribute effectively to reservoir characterization projects and make informed decisions to optimize reservoir performance.

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