Lecturer:
- Dr. Phạm Thành Sơn (ANU)
Organizers:
- A/Prof. Phó Đức Tài (HUS)
- A/Prof. Lê Hồng Phương (HUS)
- Dr. Nguyễn Thị Minh Huyền (HUS)
- A/Prof. Trần Thanh Tuấn (HUS)
Venue: VNU Hanoi University of Science, 334 Nguyễn Trãi, Thanh Xuân, Hà Nội.
Time: April 21-25, 2025
This intensive one-week workshop, Introduction to Observational Seismology, is designed to equip learners with a basic understanding of concepts in observational seismology and hands-on experience with modern research tools for seismological data processing. It serves as an engaging introduction for beginners, but provides resources and materials to facilitate advanced study.
- Promote observational seismology as a computational science of passive seismic data.
- Introduce basic seismological concepts and modern practices for retrieving waveforms and metadata, as well as performing research-standard analysis.
- Hands-on experience with seismological research tools: Python, Jupyter Notebook, Google Colab, ObsPy, SeisBench.
- Introduction to geographical mapping skills + visualize scientific data, including skills to (1) draw a geophysical map for a region of interest, (2) plot scientific data on a map.
- Introduction to digital seismic data, including (1) principles of seismometry, (2) seismic data as digital signals, (3) global seismic databases, and (4) basic data processing tools.
- Introduction to inverse problem theory with demonstration for (1) polynomial parameter estimation and (2) earthquake location determination.
- Introduction to cross-correlation techniques (1) theory and example of autocorrelation for shallow Earth imaging, and (2) single-event global correlogram.
- A brief introduction to machine learning in seismology, including (2) the PKIKP onset picker and (2) automatic earthquake detection with the Seisbench framework.
Dr. Phạm is an observational seismologist, who uses seismic waves to understand the Earth’s interior structures and seismic energy sources using mathematical tools, such as signal processing, numerical modeling, and geophysical inference. He is particularly interested in structures and processes a few kilometers beneath the surface, such as polar ice sheets, down to the Earth’s deepest shell, including its cores. To date, one of his visible contributions is to help understand better the architecture of the seismic wavefield several hours after large earthquakes and use it to decipher several long-lasting puzzles regarding the Earth’s inner core. In current and near-future research, he aims to expand my seismological toolbox to advance research on the topics, focusing on understanding the structures and dynamics of the polar ice sheets in Antarctica and Greenland in the changing climate.
Here I compile a list of some reading materials about some useful tools in observational seismology:
- What's inside the Earth: Interactive poster link
- Coding environment: Jupyter Notebook link to tutorial
- Free cloud server: Google Colab link to tutorial
- Basic mapping tool: Basemap link to tutorial
- Theoretical travel time and ray paths: Obspy Taup link to tutorial
- Access to seismic data servers: Obspy FDSN Client link to tutorial
- Efficient Bayesian sampler: emcee link to tutorial
- Google machine learning crash course link to tutorial
- Machine Learning Cơ Bản by Vũ Hữu Tiệp link to ebook
- Seisbench: A toolbox for machine learning in seismology link
More up-to-date reading list can be found in this Google Docs.
Module 1: Introduction, geographical mapping
- Lecture slides PDF PPTX
- In-class exercise: Plotting Maps: Seismograph and Seismicity in Vietnam
- Self-practice exercise: Exploring seismic stations in Antarctica
Module 2: Ray theory, seismometry, seismic databases
- Lecture slides PPTX (download to view)
- In-class exercise: Ray theoretical travel times and paths
- Self-practice exercise: Triangulation of M5.2 Kon Tum 28/07/2024 earthquake
Module 3: Geophysical inverse problem
- Lecture slides PPTX (download to view)
- In-class exercise: Linear regression
- Self-practice exercise: Earthquake location as an inverse problem
- Advanced exercise: Seismic moment tensor inversion (by Julien Thurin)
Module 4: Seismic interferometry and study of the Earth’s structures
- Lecture slides PPTX (download to view)
- In-class exercise: Teleseismic P-wave coda autocorrelation
- Self-practice exercise: Single-event global correlogram
Module 5: Machine learning in Seismology
- Lecture slides PPTX (download to view)
- In-class exercise: Convolutional neural network for PKIKP onset phase picker
- Self-practice exercise: Introduction to seisbench: A toolbox for machine learning in seismology
- Bonus project: Automatic picking of micro icequakes