Advanced Geostatistics for Reservoir Characterization | Training course
Learn the state-of-the-art in reservoir characterization and property and facies modeling using the stochastic simulations.
- Generate robust 3D reservoir static models using standard and advanced geostatistical simulation techniques. Discuss their pros and cons.
- Improve model quality by integrating various data sources in the interpolation process and filtering seismic data.
- Perform facies modeling with a focus on the analysis of proportion curves and the role of the stratigraphic reference surface.
- Learn simulation techniques to populate the model with petrophysical properties constrained by the facies distribution.
- Introduction to the different concepts through a step by step workflow analysis and description.
- Half of the course is devoted to theoretical and methodological presentations, the second half to practical exercises on real-life cases to deepen the understanding of concepts. The focus is on illustrations and practical contributions of the covered concepts.
- Computer exercises with Isatis.neo Petroleum Edition.
- Course material provided (documentation, journal files, training data, worked examples) for re-use in your workplace.
Who should attend
This course aims at geologists, geophysicists and reservoir engineers involved in reservoir characterization.
DAY 1: HORIZON MAPPING AND GEOPHYSICAL RESERVOIR CHARACTERIZATION
- Overview of the standard geomodeling workflow
- Data integration techniques (kriging in the multivariate case, kriging with external drift and kriging with Bayesian drift, kriging with uncertain data) with application examples in Time-to-Depth conversion and regional integration of seismic data
- Introduction to geostatistical filtering of seismic data with factorial kriging
- Application of geostatistical simulations for assessing uncertainty on maps
DAY 2: POPULATING A GEOLOGICAL MODEL WITH FACIES
- Facies definition from logs with a geostatistical clustering technique
- Presentation of facies distribution modeling concepts
- Common simulation algorithms for categorical variables (facies)
– Indicator simulations (SIS)
– Truncated Gaussian (TGS) and Plurigaussian (PGS) simulations
– Boolean simulations (object-based)
– Multiple-Point Statistics (MPS)
– Process-based approaches (Flumy)
- Accounting for structural constraints in facies modeling
DAY 3: POPULATING A GEOLOGICAL MODEL WITH PROPERTIES – CONNECTIVITY INTEGRATION
- Advanced analysis of petrophysical properties in facies
- Common simulation algorithms for petrophysical properties
- Volumetrics and quantification of the associated uncertainty
- Accounting for dynamic data (honoring connectivity information)
As the course refers to advanced geostatistical concepts, it is highly recommended that attendees have a reasonable knowledge of variography and kriging.
The course “Basic Concepts of Oil & Gas Geostatistics” covers the fundamental concepts of geostatistics for Oil & Gas and provides an ideal basis to this course.