ROSE School: Computational Geophysics and Data Analysis

ROSE School: Computational Geophysics and Data Analysis

Prof. Dr. Heiner Igel and Moritz Beyreuther, LMU Munich

Last update: December 01, 2009

November 30 – December 11, 2009

Scope: The course aims to provide students with an understanding of the principles of digital signal processing, filter theory and the application of spectral methods in the analysis of geophysical data. Topics include discrete Fourier transforms, convolution, power spectra, transfer functions, covariance, correlation, Laplace transforms, Z-transforms, filters, deconvolution, basic statistics, model fitting via singular valued decomposition and probabilistic methods. The lectures are complemented by practicals with data examples from major recent earthquakes (e.g., the great Andaman M9.3 earthquake), as well rotational seismology, and computational wave propagation.

Tentative Lecture Plan (L – Lecture, T- Tutorial)

Day/Time	9:00-10:30	11:00-12:30	14:00-15:30
Mon, 30. Nov	L1	L2	T1
Tue, 1. Dec	L3	T2	L4
Wed, 2. Dec	L5	T3	L6
Thu, 3. Dec	L7	T4	L8
Fri, 4. Dec	L9	T5	T5

Mon, 7. Dec	L10	T6	L11
Tue, 8. Dec	L12	L13	T7
Wed, 9. Dec	L14	T8	T8
Thu 10. Dec	Exam
Fri 11. Dec

Minimum total lecture time: 21 hrs

Minimum total tutorial time: 12 hrs

Lecture and tutorial outline, literature, additional material and links:

Literature:

Most of the graphics are taken from the following books, additional material is given with each lecture or tutorial:

Stein and Wysession, An introduction to seismology, earthquakes and earth structure, Blackwell Scientific (Chapts. 6, 7 and appendix) see also http://epscx.wustl.edu/seismology/book/ (several figures here taken from S+W).

Shearer, Introduction to Seismology, Cambridge University Press, 1990, 2^nd edition 2009 (section on data processing and appendices)

Tarantola, Inverse Problem Theory and Model Parameter Estimation, SIAM, 2005 (probabilistic inversion, examples in the appendix)

Gubbins, Time series analysis and inverse problems for geophysicists, Cambridge University Press (e.g., Z-transforms, geophysical applications)

Scherbaum, Basic concepts in digital signal processing for seismologists (e.g., seismometer equation, instrument corrections).

Scherbaum, Of Poles and Zeros, Fundamentals of Digital Seimology, Springer 2007

Schuster: Seismic Interferometry (Cambridge University Press), using correlation techniques for tomography

Excellent material can be found online here:

http://www.seismo.ethz.ch/staff/jclinton/GDP07/GDP07.html (Course on Geophysical Data Analysis by John Clinton, ETH, e.g. Laplace- and z-transforms)

Links to pdfs with the folders containing slides and additional material are given below. Note that some of the slide shows are unfinished and will be further updated. Also note that maths details will be given on the board.

Note: links below not operational until Tue November 24!

Week 1:

Day 1:

L1: Introduction: What are the current hot topics of seismology and what role do computations and data analysis play?

L2: Mathematical background for data analysis and inverse problems

T1: Maths exercises: complex numbers, linear algebra, matrices and vectors, eigenvector analysis, applications to geophysical problems

Day 2:

L3: Data in seismology: networks, observables.

T2: Introduction to Python, ObsPy and Arclink

L4: Seismic instruments, instrument response

Day 3:

L5: Generating synthetic seismograms: an introduction