Geostatistical Seismic and Rock Physics Inversion
Instructor: Dr. Dario Grana (University of Wyoming, United States)
Date
Monday, 5 October 2026, 09:00 - 17:00 (exact timing TBA)
Discipline
Geophysics – Reservoir Characterization
Level
Intermediate
CPD Points
5
Meet the instructor
"Welcome to the course Geostatistical Seismic and Rock Physics Inversion. This course introduces modern inversion frameworks that integrate seismic data, rock physics modeling, and geostatistical simulation. By the end of the course, attendees will understand how to formulate inversion problems, incorporate prior geological knowledge, quantify uncertainty, and interpret posterior solutions for reservoir characterization"
Dario Grana is an associate professor in the Department of Geology and Geophysics at the University of Wyoming. He received a MS in Mathematics at University of Pavia (Italy) in 2005, a MS in Applied Mathematics at University of Milano Bicocca (Italy) in 2006, and a Ph.D. in Geophysics at Stanford University in 2013. He worked four years at Eni Exploration and Production in Milan.
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.
