Applied Geostatistics
Consultant/Trainer: Barrie Wells/Thomas Jerome
The Petrogenium (in collaboration with EPTS) Applied Geostatistics course participants will gain a practical understanding of how to select and apply appropriate geostatistical techniques for exploration and production tasks such as mapping, reservoir simulation, basin modeling, and spatial data analysis—without needing to master the underlying mathematics or algorithms.
Participants
This Petrogenium course aims at Petroleum geologists and other geoscientists preparing data for use in reservoir simulators and basin models. Anyone wishing to gain the best insight into and obtain the most value from their geo-spatial data.
Learning Objectives
The course aims to provide knowledge of how to apply the various tools known as geostatistics, using both readily available software and more specialist packages.
The emphasis is on practical application and understanding of context over a consideration of the mathematics. A multitude of software-based exercises give a practical introduction to what is available and provide useful tools to take back to the workplace.
- What is geostatistics, and how does it change our appreciation of familiar tasks and tools?
- How geostatistics aids in understanding trends in spatial data-sets:
- Classical multivariate statistics
- Conditional distributions
- Direct simulations
- Variogram analysis
- Modelling anisotropy
- Understanding the effects of scale:
- Heterogeneity and discontinuity
- Data scale versus modelling scale
- Upscaling for efficient modelling
- Allowing for spatial trends in gridding & contouring:
- Honouring data or minimising errors
- Using kriging to make better maps
- Making use of new data:
- Bayesian and geo- statistics;
- History matching
- Sequential / Indicator simulation
- Quantifying uncertainty:
- How geostatistics includes methods for uncertainty quantification
- Using Monte Carlo and other stochastic simulations
Programme
- What is geostatistics, and how does it change our appreciation of familiar tasks and tools?
- How geostatistics aids in understanding trends in spatial data-sets:
- Classical multivariate statistics
- Conditional distributions
- Direct simulations
- Variogram analysis
- Modelling anisotropy
- Understanding the effects of scale:
- Heterogeneity and discontinuity
- Data scale versus modelling scale
- Upscaling for efficient modelling
- Allowing for spatial trends in gridding & contouring:
- Honouring data or minimising errors
- Using kriging to make better maps
- Making use of new data:
- Bayesian and geo- statistics;
- History matching
- Sequential / Indicator simulation
- Quantifying uncertainty:
- How geostatistics includes methods for uncertainty quantification
- Using Monte Carlo and other stochastic simulations