petrel introduction course guide
TRANSCRIPT
Introduction Petrel Course (UAB-2014)
This course has been prepared as an introduction of Petrel software (Schlumberger,
www.software.slb.com/products/platform/Pages/petrel.aspx), an application which allows
the modeling and visualization of reservoirs, since the exploration stage until production,
integrating geological and geophysical data, geological modeling (structural and
stratigraphic frameworks), well planning, or property modeling ( petrophysical or
petrological) among other possibilities.
The course will be focused mainly in the understanding and utilization of workflows aimed
to build geological models based on superficial data (at the outcrop scale) but also with
seismic data. The course contents have been subdivided in 5 modules each one
developed through the combination of short explanations and practical exercises.
The duration of the course covers more or less 10h divided in three sessions. The starting
data will be in the first week of December.
This course will be oriented mainly for the PhD and master students ascribed at the
Geologic department of the UAB. For logistic reasons the maximum number of places for
each torn are 9. The course is free from the Department members but the external
interested will have to make a symbolic payment.
Those interested send an e-mail to the Doctor Griera ([email protected]).
The course will be imparted by Marc Diviu (Msc. Geology and Geophysics of reservoirs).
Contents
Introduction
- Petrel interface: menus, layout, templates, bars and windows
- Auto-save, workflows and available processes
Module 1:
- Load & Edit data
- Digital mapping
- Reconstruct & edit surfaces
o True stratigraphic thickness maps
Module 2
- Make a simple grid
- Make Layering
- Property Modelling
- Insert inline intersections or cross-lines
Module 3: Fault Modelling
o Pillar Gridding
o Layering
o Faulted Horizons
Module 4: Seismic Treatment
o Load & Edit data
o Fault interpretation
o Horizon interpretation
o Surface reconstruction
Module 5: Facies Modelling
o Truncated Gaussian Algorithm with trends
o Filtering
o Zonations