Advanced Mapping Techniques and Uncertainty Quantification for Reservoir Modeling
Learn how to generate maps combining various sources of different accuracy data and how to quantify uncertainty.
DURATION: 4x2-hour sessions over 4 consecutive days | LEVEL: ADVANCED
Following this course, you will know how to combine different sources of data to compute accurate maps (or cubes). You will get hints on how to account for data varying accuracy to quantify the result uncertainty at each point of the map (or cube).
- Kriging with uncertain data (measurement errors)
- Mapping with data and inequalities:
– Combining hard data and intervals
- Mapping with sparse data
- Demonstration with Isatis: Mixing certain and fuzzy data with trends
- Kriging with trend: Use of the Bayesian framework for the drift:
– Kriging with Bayesian drift vs Kriging with external drift
– Practical use of a Bayesian drift
- Local geostatistics:
– Determining local values for kriging parameters
– Impact of the use of local parameters
- Simulations theory:
– Limitation of Kriging – introduction to simulations
– Simulation techniques for continuous variables
– Use of simulations for quantifying uncertainty on a map
- Demonstration with Isatis: Uncertainty calculation on a map accounting for local uncertainty on each point of an external drift
- Use of simulations for Uncertainty analysis:
– Uncertainty analysis methods
– Probability and quantile maps
– Mapping uncertainty and risks
- Demonstration with Isatis: Quantile maps and risk curves
Knowledge of Kriging theory and practice.
The course is delivered in one-to-one 4×2-hour online training sessions over 4 consecutive days by our experienced instructors.
You only need an internet connection and headphones with a microphone.
Although examples are given with Isatis software, the concepts and methodologies that will be addressed can easily be applied using your usual geomodeling software package.
This course is part of a live online training program to quickly get acquainted with the essential concepts and methodologies of geostatistics applied to reservoir characterization and modeling.
Courses are given as one-to-one sessions for quality content, better suited to your needs and issues, and facilitated exchange between trainee and trainer.
Note that if the provided scheduled dates are not compatible with your agenda, we invite you to contact us to arrange your own schedule. Course content may also be adapted to your needs on demand.
To learn the fundamentals of geostatistics:
- Basic concepts of geostatistics – Data analysis and variography
- Kriging and cokriging theory and best practices
To go further with geostatistics:
- Advanced mapping techniques and uncertainty quantification
- Geostatistical filtering of seismic data
- Populating a geological model with properties
- Geostatistical simulation post-processing | Integration of dynamic data.