Constructing a reservoir model includes the difficult task to integrate data from very different sources like seismic, well, core and wireline information as well as sedimentological concepts and facies interpretations. This course will show how modern reservoir modelling practice handles such different viewpoints from geoscience and engineering. The course starts with characterising reservoirs in terms of structure, sedimentology and related petrophysical properties and develops these into static reservoir models. Geostatistics and data integration across the key disciplines will set the baseline. This training will teach state-of-the-art concepts, practical fundamentals and common pitfalls when using applications in integrated computer-based modelling. It aims to cover deterministic and stochastic techniques in reservoir modelling and shows how to apply these for populating facies, and properties like porosity, permeability or saturation. The workshop character will be emphasized by showing best practices for constructing useful static geomodels in Petrel software, which are ready to be initialised as simulation models.
Course Level: Skill Instructor: Wilfried Gruber
Designed for you, if you are...
A geologist, geophysicist or petroleum engineer seeking to gain an understanding and practical knowledge in reservoir characterisation, geostatistics and modelling
This course provides a thorough introduction and covers all aspects, from basics, statistical methods right through to the application of geostatistics in reservoir modelling.
How we build your confidence
Emphasis will be on practical examples in order to improve personal skills in reservoir modelling.
At the same time, theory in statistics, geostatistics, interpolation and simulation techniques will be communicated to provide a firm knowledge base.
The course is designed in a way that each main topic will consist of a theory section followed by computer exercises for application of the learned and opportunities for in-depth discussions.
The benefits from attending
At the end of the course, you will have confidence on how to characterise, model and manage reservoirs using geostatistics. The key points to take will be:
Showing the methods and benefits of integrating geological, geophysical, petrophysical and engineering data into static reservoir models
Introducing state of the art deterministic and stochastic modelling techniques, demonstrating their application and outcomes
Gaining skills on making realistic assumptions of reservoir parameters and the associated spread of model uncertainties
Discussing the full workflow from data input and analysis through modelling and upscaling results into a model ready for flow simulation
Introduction to reservoir characterisation
Reservoir metrics and related variable types
Geostatistics and spatial data analysis
Variograms, Kriging basics and methods, Co-kriging