GEOLOGICAL MODELING
MODELLIZZAZIONE GEOLOGICA
| A.Y. | Credits |
|---|---|
| 2017/2018 | 6 |
| Lecturer | Office hours for students | |
|---|---|---|
| Luca Lanci |
Assigned to the Degree Course
| Date | Time | Classroom / Location |
|---|
| Date | Time | Classroom / Location |
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Learning Objectives
The course is aimed at the acquisition of the principles of analysis of regionalized variables and discrete time series, addressed to a geological-stratigraphic and paleoclimatic context. The course also aims at mastering the main numerical analysis tools and provides numerous practical examples with the help of a standard programming language for data analysis (Matlab). The numerical analysis principles in this course have potential applications in many other fields and are an important tool for quantitative analysis.
Program
The course will have a practical and computer-aided approach to the following topics :
1. Introduction to geostatistics
1.1. Semivariogram.
1.2. Anisotropy
1.3. Ordinary Kriging
1.4. Universal Kriging
2. Introduction to the time series analysis.
2.1. Introduction to discrete time series
2.2. Fourier transform.
2.3. Power spectrum estimate (WOSA) .
2.4. Multi Taper Method (MTM).
2.5. Noise and Signal.
2.6. Evolutive spectrum.
2.7. Wavelets.
2.8. Singular Spectrum Analysis.
Bridging Courses
None
Learning Achievements (Dublin Descriptors)
· The student must demonstrate the ability to master the numerical analysis methods envisaged by the course program.
· The student must demonstrate the understanding of concepts and theories studied in the course; He/she must be able to independently analyze complex data sets by choosing the appropriate tools for specific cases; He/she must be able to evaluate the significance of the results.
· The student must demonstrate possession of the ability to use knowledge and concepts that will allow him/her to reason according to the logical specificity of the discipline. In particular, he/she should be able to identify the methodologies appropriate to the contexts and to propose hypotheses of analysis of non trivial cases.
Teaching Material
The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it
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