NFYK15017U Probabilistic methods in Geosciences
The objective of the course is to provide the background needed for allowing probabilistic integration of GEO-information from diverse sources. Such GEO-information can be geophysical data (reflection seismic data, well log data, EM data,..) and geological information (information about realistic spatial structures given geological knowledge). First theory and methods for characterizing such different information in a probabilistic form will be presented. Then methods enabling the student to integrate this information into one probabilistic model, consistent with all information at hand, will be given.
This course aims to provide the student with skills to
- describe available geo-information using statistical methods
- understand and apply geostatistical simulation algorithms, to describe and simulate geologically realistic structures (using Gaussian and multiple-point statistical models)
- understand and quantify errors in physical models related to data uncertainty and modeling uncertainty
- integrate information based on structural geological information and geophysical observations.
- solve non-linear inverse problems with non-Gaussian a priori models
- analyze and validate results from probabilistic inverse problems
The course will provide knowledge about geostatistics and probabilistic inverse problem theory.
The student will acquire skills to a) describe information in a statistical form using classical statistical models and geostatistical models, and b) apply and evaluate these methods for practical applications in Geosciences.
Tarantola (2005) Inverse Problem Theory
Lecture notes: probabilistic integration of geo-data
may be useful: NFYK13011U Applied Statistics: From Data to Results
- 7,5 ECTS
- Type of assessment
- Continuous assessmentOral examination, 30 minutes3 projects (group or individual) [weighed by 12.5%, 12.5% and 25%] followed by 1 individual oral examination [weighed by 50%]
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
several internal examiners
Same as ordinary exam. The student can choose to re-use points from projects handed in during the course, or make new projects.
Criteria for exam assesment
- Practical exercises
- Project work