The seismic signal carries a large amount of information from the subsurface. Seismic attributes aim to assess this information for utilisation during reservoir characterisation. Reservoir geologists need to understand seismic attributes and integrate seismic amplitude behaviour into reservoir studies. This course covers those sets of attributes typically used for reservoir characterisation and indicates their application in reservoir modelling. A nearly infinite number of seismic attributes is technically possible. Not all of them are meaningful, some are redundant, and other attributes work in specific situations only. The participant’s intuition for seismic amplitude will be trained systematically by starting from simple instantaneous attributes and evolving via amplitude versus offset methods to advanced seismic inversion studies. Hands on real data exercises demonstrate how attributes relate to reservoir occurrence, rock and fluid properties and their heterogeneity. Examples include exploration scenarios and will link seismic and well data for quantitative interpretation. In modern reservoir characterisation, which aims for complete data integration, validated attributes are key to understanding the inter-well space.
Course Duration: 5 days
Course Level: Skill Instructor: Wilfried Gruber
Designed for you, if you are...
A geoscientist (all disciplines) who is exposed to reservoir description, characterisation and modelling
How we build your confidence
The methodologies presented are aimed to the point where seismic is incorporated into the geoscience workflow.
The course format contains theory, example cases from field studies and literature.
In practical examples you will use seismic attribute software to apply the methods taught, strengthen the knowledge gained, and set the basis for a maximum of seismic data integration in upcoming projects.
Throughout the course, the level of detail in viewing the reservoir increases. It starts with seismic attributes giving field scale trends, moves on to integrating well data for resolving local features and finally embarks on statistical methods to be utilised on meter scale grid models.