(Click Category to List Courses)
7 - OGE-R - Oil & Gas - Reservoir Engineering
OG-R 106 - Geostatistics and Reservoirs Modeling
| Code | Start Date | Duration | Venue | |
|---|---|---|---|---|
| OG-R 106 | 07 July 2025 | 5 Days | Istanbul | Registration Form Link |
| OG-R 106 | 01 September 2025 | 5 Days | Istanbul | Registration Form Link |
| OG-R 106 | 27 October 2025 | 5 Days | Istanbul | Registration Form Link |
| OG-R 106 | 22 December 2025 | 5 Days | Istanbul | Registration Form Link |
Please contact us for fees
Course Description
This course is designed to provide a solid understanding of reservoir description and modeling for effective reservoir management. Participants will learn the fundamental concepts of geostatistics, including data analysis, variogram modeling, kriging techniques, and stochastic simulations. The course emphasizes integrated studies, uncertainty analysis, and real-world case studies, enabling participants to make informed decisions for reservoir development and optimization.
Course Objectives
- Apply reservoir description and modeling techniques to support reservoir management.
- Recognize the limitations and opportunities of geostatistical reservoir modeling.
- Understand the principles of statistics and probability as applied to reservoir modeling.
- Use variogram modeling for spatial correlation analysis in reservoir characterization.
- Apply kriging techniques for property estimation at unsampled locations.
- Implement stochastic simulation methods for uncertainty quantification.
- Develop integrated reservoir models to support decision-making in field development.
Who Should Attend?
- Petroleum Engineers
- Geophysicists
- Geologists
- Reservoir Engineers
- Processing Engineers
- Mining Engineers
- Data Scientists & Analysts
Course Details/Schedule
Day 1
- Introduction to reservoir modeling
- Basic statistical principles
- Probability theory in reservoir modeling
- Types of reservoir models
- Data collection & integration
- The role of geological, petrophysical, and production data
Day 2
- Data analysis & variogram modeling
- Data quality control & preprocessing
- Handling missing and inconsistent data
- Exploratory Data Analysis (EDA) trends, outliers, and biases
- Variogram modeling fundamentals and interpretation
- Spatial correlation & anisotropy
- Detecting directional trends in reservoir data
- Experimental & modeled variograms
Day 3
- Kriging techniques
- Co-kriging & indicator kriging
- Multi-variable property estimation
- Stochastic simulation
- Case studies in kriging & simulation
- Introduction to uncertainty analysis
- Methods for quantifying model uncertainty
Day 4
- Overview of integrated studies
- Combining geological, geophysical, and engineering data
- Spatial and structural modeling
- Grid-based and object-based approaches
- Reservoir zonation & facies modeling
- Defining heterogeneous reservoir units
- Estimation of properties at well locations
- Upscaling and data interpolation
- Well placement & optimization strategies
- Impact of modeling on field development
Day 5
- Conditional simulation & facies modeling
- Defining rock types and flow units
- Petrophysical property simulation
- Modeling porosity, permeability, and saturation
- Ranking of realizations
- Construction of reservoir simulator input model
- Future predictions & uncertainty quantification
- Risk assessment for reservoir development
