Applied Geostatistics for Oil and Gas
Select Other "city & date"
Applied Geostatistics for Oil and Gas Course
Introduction:
The term Geostatistics is very versatile and can be looked at from different points of view. The applied Geo-statistics field, especially for oil and gas, will be discussed during the course with a great emphasis on the reservoir modeling, 4 D Seismic applications, Mud logs and E logs
Application of geostatistical techniques to build reservoir models through the integration of geological, core/well log, seismic and production data to generate a consistent reservoir description. Introduces reservoir modeling workflow from the construction of the 3D static reservoir model through upscaling and dynamic reservoir simulation.
It provides background and insights to geostatistical modeling techniques and the situations where the application of geostatistics could add value. Provides guidance in the assembly and analysis of the required data for geostatistical techniques and the resulting numerical models. Includes extensive hands-on training and problem solving using public domain software. If available, commercial software (typically PETREL) is used to demonstrate the workflow with a field example.
Course Objectives:
The main objective of this course to use all data, techniques, and tools to applications and tasks rather than mathematics and algorisms behind it. Learning how to be a member in a real team by the cooperation of all branches (Geophysics, Geology, Petrophysics and reservoir engineer) to build better geological models, and then go through reservoir simulation
Who Should Attend?
Practicing reservoir and production engineers, Geologist, Petrophysics and geoscientists working as a part of an integrated reservoir management team
Course Outlines:
Introduction
- Role of geostatistics in reservoir modeling
- Review of steps in building static reservoir model
- Decision making under uncertainty
- Review of probability and distributions
- Univariate analysis/data transformation, Q-Q plot, P-P plot
- Analysis of field data
- Bivariate statistics
- Conditional expectation
- Covariance and Correlation
- Analysis of spatial continuity
- Variogram definition, physical meaning
- Calculating & interpreting the variogram
- Modeling variograms
- Simple and ordinary kriging
- Cross-validation
- Analysis of field data
- Point & block estimation
- Cokriging/Collocated Cokriging
- Conditional simulations/sequential approaches
- Indicator simulation of lithofacies
- Boolean/Object-based models
- Multipoint Geostatistics
- Analysis of Field Data
- Demonstration of the workflow with a field example using PETREL (if available)
- Multidisciplinary Data Integration
- Data Correlation/Electrofacies Classification
- Integration of Seismic Data
- Upgridding and Upscaling
- Flow simulation through geologic models using streamlines
- Experimental design and applications
- History matching- preliminaries
- Course Summary & conclusions
