EAGE Short Course Geostatistical Reservoir Modeling and Uncertainty Quantification
25 October 2020 | Porto, Portugal
Geostatistical Reservoir Modeling and Uncertainty Quantification
Instructor: Dr Dario Grana (University of Wyoming, United States)
Duration
1 Day
Discipline
Geophysics – Reservoir Characterization
Level
Intermediate
CPD Points
5
Course description
Reservoir modeling provides a set of techniques to create three-dimensional numerical earth models in terms of elastic, petrophysical and dynamic properties of reservoir rocks. Mathematical/physical models of the reservoir are generally uncertain due to the lack of information, noise in data measurements, approximations and assumptions. The course focuses on geostatistical methods for reservoir modeling and uncertainty quantification techniques for reservoir predictions.
It is divided into four main parts: Geostatistical methods for interpolation and simulation; Rock physics modeling; Geophysical inverse problems; Uncertainty quantification.
Uncertainty propagation from measured data, through physical models to model predictions will be studied with a focus on seismic data inversion, static reservoir characterization, structural modeling, dynamic fluid simulation, and time-lapse monitoring. Real case studies will be presented for each topic to illustrate the proposed workflows
Course description
Reservoir modeling provides a set of techniques to create three-dimensional numerical earth models in terms of elastic, petrophysical and dynamic properties of reservoir rocks. Mathematical/physical models of the reservoir are generally uncertain due to the lack of information, noise in data measurements, approximations and assumptions. The course focuses on geostatistical methods for reservoir modeling and uncertainty quantification techniques for reservoir predictions.
It is divided into four main parts: Geostatistical methods for interpolation and simulation; Rock physics modeling; Geophysical inverse problems; Uncertainty quantification.
Uncertainty propagation from measured data, through physical models to model predictions will be studied with a focus on seismic data inversion, static reservoir characterization, structural modeling, dynamic fluid simulation, and time-lapse monitoring. Real case studies will be presented for each topic to illustrate the proposed workflows
Course objectives
- Generate multiple reservoir models
- Understand physical relations between reservoir and geophysical parameters
- Evaluate the uncertainty of model predictions
Course outline
- Generate multiple reservoir models
- Understand physical relations between reservoir and geophysical parameters
- Evaluate the uncertainty of model predictions
- Introduction
- Part 1: Review of statistical analysis and probability
- Part 2: Geostatistics and spatial uncertainty
- Part 3: Rock physics
- Part 4: Geostatistics and spatial uncertainty
- Part 5: Seismic inversion
- Part 6: Uncertainty quantification
- Part 7: Visualizing uncertainty
Prerequisites
Participants should have knowledge of basic reservoir modeling concepts and of common geophysical data.
Participants' profile
The course is designed for employees of oil companies in geophysics and reservoir modeling.