Undergraduate Course: Geophysical Imaging and Inversion (EASC10109)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This is a companion course to Geophysical Measurement and Modelling. That course teaches physics and how to represent/model it computationally, this course teaches how to combine that information with new measurements to constrain model parameters for applications in remote sensing in the atmosphere, on the Earth's surface or in the subsurface. Such skills underpin much of science in all of the Geophysical disciplines taught in the SH year. |
| Course description |
An integrated introduction to imaging and inversion theory at honours level. The course begins with an overview of the difference between various ways to image a medium or constrain a model: converting the inverse problem to a forward problem, or applying inverse theory with decreasing degrees of approximation (linearization error).
It then introduces seismic imaging since this is the main application that traditionally uses the ¿forward problem¿ approach, Thereafter inverse theory is introduced, progressing from linearised methods to iterated-linearised methods to non-linearised methods. Bayesian methods are introduced, including relevant associated probability theory. Finally, the inversion approach is linked back to the migration theory: it is shown that migration can be considered as the first step in an iterated-linearised waveform inversion for image parameters (impedances).
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Information for Visiting Students
| Pre-requisites | Good grounding in Maths and Physics to second year level |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2022/23, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 27,
Seminar/Tutorial Hours 7,
Supervised Practical/Workshop/Studio Hours 9,
Feedback/Feedforward Hours 3,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
148 )
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| Assessment (Further Info) |
Written Exam
60 %,
Coursework
40 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Exam (60%); Coursework (40%)
Coursework (40%) This is broken down into:
¿ One individual exercise (20%)
¿ One group exercise (20%)
Assessment Deadlines
Individual Exercise ¿ Semester 2, Week 5 ¿ Friday (submit online via Turnitin/Learn)
Group Exercise ¿ Semester 2, Week 9 (during timetabled class)
Written Exam ¿ Semester 2, May Exam Diet
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| Feedback |
Homework problems will be set each week, with the answers provided later, allowing students to generate their own feedback. The individual coursework exercise will be marked and returned as usual. The group exercise will be assessed with feedback from both staff and students in the audience. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand how to combine the information in modelled representations of physics with measured data
- Impose constraints from data on model parameters
- Apply practical skills in data analysis
- Demonstrate knowledge of several applications of inverse methods, including seismic imaging and remote sounding of the atmosphere
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Reading List
Time Series Analysis and Inverse Theory for Geophysicists by David Gubbins. (Cambridge University Press)
Inverse Problem Theory and Methods for Model Parameter Estimation by Albert Tarantola. |
Additional Information
| Graduate Attributes and Skills |
1. Knowledge of mathematics and probability for application to a variety of practical problems
2. Team-working on technical problems
3. Confidence in presenting mathematical results verbally.
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| Keywords | Inversion,imaging,Bayesian,parameters,constraint,conditioning,eigenvalues,eigenvectors |
Contacts
| Course organiser | Dr Hugh Pumphrey
Tel: (0131 6)50 6026
Email: |
Course secretary | Ms Katerina Sykioti
Tel: (0131 6)50 5430
Email: |
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