(Click Category to List Courses)
8 - OGE-R - Oil & Gas - Reservoir Engineering
OG-R 136 - Geostatistics, Data Integration and Reservoir Modeling (10 Days)
| Code | Start Date | Duration | Venue | |
|---|---|---|---|---|
| OG-R 136 | 21 October 2024 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 18 November 2024 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 16 December 2024 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 20 January 2025 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 17 March 2025 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 12 May 2025 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 07 July 2025 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 01 September 2025 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 27 October 2025 | 10 Days | Istanbul | Registration Form Link |
| OG-R 136 | 22 December 2025 | 10 Days | Istanbul | Registration Form Link |
Please contact us for fees
Course Description
Geostatistics, Data Integration and Reservoir Modeling is a course that focuses on the application of geostatistical techniques to integrate various types of data in reservoir modeling for the oil and gas industry. The course covers topics such as spatial data analysis, variogram modeling, kriging, simulation, uncertainty analysis, and reservoir characterization. Participants will learn how to use geostatistical methods to analyze and interpret subsurface data, build reservoir models, and make informed decisions in reservoir management. The course also emphasizes the importance of data integration and quality control in the modeling process.
Course Objectives
- Learning depositional and petrophysical facies modeling
- Building structural and stratigraphic models
- Building up a complete model for simulation
- Learning stochastic and deterministic modeling methods
- Learning uncertainty mitigation by generating realizations or scenario, ranking
- Learning how to apply reservoir description and modeling to support reservoir management
- Recognizing the limitations and opportunities of reservoir modeling.
- Learning the Kriging techniques
- Understanding the statistics and probability
Who Should Attend?
- Petroleum/ Geophysicists/ Geologists/Reservoir engineers
- Technical/ reservoir engineers
- Processing engineers
- Commercial analysts
- Decision makers/ investors in oil and gas sector
Course Details/Schedule
Day 1
- Introduction to Geological Modeling
- Software Interface
- Data QC, Editing, Import and Statistical Analysis
- Spatial data analysis
Day 2
- Well Correlation
- Fault Modeling
- Pillar Gridding
- Horizoning
Day 3
- Layering
- Geometrical Modeling
- Well Logs or Data Point Up-Scaling
- Facies Modeling
Day 4
- Data Analysis - Variogram Modeling
- Concept of variograms and covariance functions
- Variogram modeling techniques
- Interpretation of variogram models
Day 5
- Petrophysical Property Modeling (Interpolation Algorithms)
- Volume Calculations
- Plotting - Property QC
- Workflows
- Uncertainty Mitigation
Day 6
- Theory and principles of kriging
- Ordinary kriging
- Universal kriging
- Other kriging techniques
- Application of kriging in reservoir modeling
Day 7
- Spatial Modeling
- Overview of Integrated Studies
- Structural Modeling
- Estimation of Properties at Well Locations
Day 8
- Reservoir Characterization
- Building reservoir models using integrated data
- Reservoir property estimation and uncertainty assessment
- Decision-making in reservoir management based on model results
Day 9
- Project Work
- Application of geostatistical techniques to a reservoir modeling project
- Presentation of project results and findings
- Peer review and feedback session
Day 10
- Conditional Simulation
- Facies/Rock Type Modeling
- Petrophysical Properties Simulation
- Ranking of Realizations
- Construction of Simulator Input Model
- Future Predictions and Quantification of Uncertainty
