A Practical Introduction of Non-Linear Geostatistics for Petroleum Reservoirs (DAT 602)
A Practical Introduction of Non-Linear Geostatistics for Petroleum Reservoirs (DAT 602)
COURSE SCHEDULE
| Code | Date | Location | price (€)* |
|---|---|---|---|
| DAT 602 | 13 - 15 May 2026 | Online | 1980 |
| DAT 602 | 15 - 17 Apr 2026 | Paris | 2640 |
COURSE OVERVIEW
This hands-on course is designed to develop practical skills in applying non-linear geostatistics to petroleum engineering problems. The course begins by examining the suitability and limitations of conventional geostatistical techniques for reservoir characterization. Participants will develop practical tools to assess whether spatial datasets satisfy the assumptions required for kriging-based geostatistics. These tools help identify situations where conventional linear geostatistical approaches may not provide the most reliable predictions of reservoir behavior.
Non-linear statistical methods are then introduced to enable participants to analyze non-linear bivariate relationships and quantify deviations from linear behavior. These techniques are particularly useful for investigating relationships such as porosity and permeability estimation from wireline logs.
The course also explains the assumption of linear spatial dependence in conventional geostatistics—what it means in practice and how to test it using commercially available software. Departures from linear spatial dependence are examined, along with their implications for reservoir flow behavior and dynamic performance.
COURSE OUTLINE
3 days
Day 1
o Statistics refresher
o An introduction to copulas
o Copulas in Excel – analysis and fitting
Day 2
o Problems with Conventional Geostatistics – How to Spot Them
o Introduction to Spatial Copulas
o Geostatistical Interpolation and Simulation Using Copulas
Day 3
o Spatial Copulas in Python – Analysis and Copula Fitting
o Copula Simulation in Python
INSTRUCTOR
Professor Stephen Tyson
Stephen Tyson is a Chair Professor in Petroleum Engineering at Universiti Teknologi Brunei, where he leads the development of teaching and research in the discipline. Previously, he served as Chair of Subsurface Modeling at the Centre for Coal Seam Gas and as Director of the Centre for Geoscience Computing in the School of Earth Sciences at The University of Queensland.
He has more than 30 years of industry experience in reservoir characterization and modeling, covering both conventional and unconventional reservoirs. His work has been primarily focused in the Asia-Pacific region and Australia.
His current research interests include model validation, verification and acceptance criteria for static and dynamic models, upscaling, uncertainty modeling, and non-linear geostatistics. He is also an Honorary Professor in Petroleum Engineering at the University of New South Wales and serves as an EAGE instructor.
FAQ
DESIGNED FOR
The course is designed for geologists and reservoir engineers who are concerned that the available geostatistics algorithms don’t create suitable representations of subsurface architectures
COURSE LEVEL
o Intermediate
LEARNING OBJECTIVES
Upon completion of this course participants will have
o An ability to describe a bivariate relationship qualitatively.
o An ability to quantify a linear bivariate relationship.
o An understanding of marginal distributions and conditional distributions and their application to geostatistics.
o The ability to define a copula and explain how this can capture a complex relationship between two variables.
REGISTER
Registration is now OPEN!
Ph.D. students, group and early bird registrants are eligible to DISCOUNT!
For more details and registration please send email to: register@petro-teach.com
REQUEST IN HOUSE
Would you like a PetroTeach training course delivered at a time or location to suit you?
click for request in house