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| Unit name |
Geophysical Data Analysis and Modelling |
| Unit code |
EASC30054 |
| Credit points |
10 |
| Level of study |
H/6
|
| Teaching block(s) |
Teaching Block 1A (weeks 1 - 6)
|
| Unit director |
Dr. Werner |
| Open unit status |
Not open |
| Pre-requisites |
EASC20041
|
| Co-requisites |
N/A
|
| School/department |
School of Earth Sciences |
| Faculty |
Faculty of Science |
Description including Unit Aims
This unit will introduce students to a range of methodologies used for the transformation and interpretation of geophysical digital data. Using a combination of lectures and computer-based practicals (using MATLAB) both the mathematic principles behind and the practical applications of these methodologies will be taught.
The course has three components. Firstly, common methodologies applied to geophysical data (including spectral methods) will be covered. The second component will introduce forward modelling, including analytical and commonly used numerical techniques such as finite-difference and finite-element models. Finally, the course will introduce the concept of inversion, and cover basic inverse theory as well as the practical aspects of its application.
Intended Learning Outcomes
On completion of the course students will:
- Understand the principles behind common time-series data processing techniques
- Understand the concept of forward modelling.
- Understand the principles behind some common forward modelling methods.
- Understand the basic principle of inversion
- Understand the mathematical basis of linear inversion
- Appreciate some of the situations which arise in the practice of inversion
- Be able to practically apply (in MATLAB) a range of common data processing algorithms
- Be able to translate a simple analytical model into code
- Be able to apply a provided more complex forward model
- Be able to write code to assess the fit of a model to some data
- Be able to run a simple iterative linear inversion to determine best fitting parameter.
Teaching Information
15 Lectures and 5 practicals
Assessment Information
- Extended practical (30%). This will be a formative MATLAB programming assignment, which will involve implementing an inversion of real geophysical data and critically assessing the results.
- 2-hour written examination (70%). This will assess the student’s understanding of the theoretical aspects of the course.
Reading and References
Recommended:
- David Gubbins: ‘Time Series and Inverse Theory’, CUP, 2006.
- Frank Scherbaum: ‘Of poles and zeros’, Springer, 2001
