Geological Data Analysis
| Title | ΑΝΑΛΥΣΗ ΓΕΩΛΟΓΙΚΩΝ ΔΕΔΟΜΕΝΩΝ / Geological Data Analysis |
| Code | GGP 433E |
| Faculty | Sciences |
| School | Geology |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Panagiotis Tsourlos |
| Common | No |
| Status | Active |
| Course ID | 40001788 |
| Academic Year | 2020 – 2021 |
| Class Period | Spring |
| Faculty Instructors |
|
| Instructors from Other Categories |
|
| Weekly Hours | 4 |
| Class ID | 600166994
|
Course Type 2016-2020
- Background
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600166994
- At the Website of the School: http://www.geo.auth.gr/courses/ggp/ggp433e/
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=11946
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
- English (Instruction, Examination)
Learning Outcomes
Upon completion of this course students 1. Will gain knowledge about the basic principles and application of selected numerical methodσ 2. can select the appropriate numeric processing technique based on the geological problem to be solved. 3. will gain basic coding skills in Matlab language to implement in practice the theory.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
Course Content (Syllabus)
• Course objectives- introduction, different types of geological data, geological data analysis process.
• Filtering procedures. Smoothing filters – differential filters. Filter class, application of moving filters, effect of filtering. Examples of application to noisy data, application to highlight changes.
• Polynomial fitting of geological data. Selection of the polynomial, fitting evaluation. Data isodistribution.
Lab Content
The laboratory cources include application of the methods taught in theory by writing code in the Matlab programing language. Students are asked to write a Matlab code that actually analyzes geodata based on techniques taught in theory and also are asked to interpret the results.
In particular, laboratories include the application of the following methods: Smoothing filters, differential filters, polynomial regression and data isodistribution, calculation of covariance and correlation, interpolation in one dimension, interpolation in two dimensions and map construction, spectral analysis (FFT) of data and application of spectral filters.
• Geostatistical data analysis. Basic statistical concepts. Spatial covariance and correlation. Interpolation in 1D. Interpolation techniques (nearest neighbor, linear, polynomial, spline etc.). Advantages and disadvantages, examples of application.
• Interpolation in two dimensions. Interpolation techniques, pros and cons. Using of covariance matrix to construct maps. Examples of application.
• Spectral analysis. Basic concepts, sampling frequency, power spectra. Application to geological. Design and application of spectral filters.
Keywords
Geological data, numerical methods, Matlab, data analysis
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Description
1)All class material is available in electronic form to all students through the course web page
2)The teacher communicates with students through email and facebook
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 59 | 2.0 | ✓ | ✓ | ✓ |
| Laboratory Work | 58 | 1.9 | ✓ | ✓ | ✓ |
| Exams | 3 | 0.1 | |||
| Total | 120 | 4 |
Student Assessment
Description
• Written final examination with a combination of questions related to theory.
• Written final examination on a computer: write a code and apply it for processing geological data
• Oral examination for students with learning disabilities.
• Intermediate written examination.
Student Assessment methods
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Problem Solving (Summative)
- Computer code writting (Summative)
Bibliography
Course Bibliography (Eudoxus)
ΑΡΙΘΜΗΤΙΚΕΣ ΜΕΘΟΔΟΙ ΜΕ ΤΟ MATLAB, Κωδικός Βιβλίου στον Εύδοξο: 21379, Έκδοση: 1η/2010
Συγγραφείς: CLEVE B. MOLER, ISBN: 978-960-461-371-7, Τύπος: Σύγγραμμα, Διαθέτης (Εκδότης): ΕΚΔΟΣΕΙΣ ΚΛΕΙΔΑΡΙΘΜΟΣ ΕΠΕ
Additional bibliography for study
MATLAB and Design Recipes for Earth Sciences: How to Collect, Process and Present Geoscientific Information. H. Trauth, Martin, Sillmann, Elisabeth. ISBN 978-3-642-32544-1, 2013. Springer-Verlag Berlin Heidelberg
Last Update
08-04-2020
