material for week 3 for the environmental data module (A. Lipp/rivers and B. Bell/seismology)
NB: the /data folder for "Seismic reflection imaging" was too big to pose on githup. You can access the data using the following Imperial File Exchange link:
On successful completion of this module, students will be able to:
- Understand common data format and database structures specific to representative fields of environmental science
- Demonstrate technical competency in handling common data types routinely encountered in the environmental sciences and identify relevant open-source data repositories
- Identify and design suitable data analysis strategies that consider data types, data distribution constraints, strength, benefits and limitations of statistical and modelling tools and environmental dynamics.
- Understand the limitation of available data and data analysis products. Understand sources of errors and demonstrate ability to comprehensively characterize uncertainties and interpret results in the context of these uncertainties, including measurement errors, environmental uncertainties as well as errors stemming from the analytical procedure itself (e.g. calibration of analysis using synthetic data/models).
Rivers networks are extremely important parts of the natural and human environment. This module will introduce a number of foundational concepts that will allow you to understand the context of much of the fluvial data you may come across. We will be drawing from geomorphology, geochemistry and hydrology. We will also discuss where data about drainage networks comes from and how it can be accessed. You will gain first hand experience of generating drainage networks from topographic data in the practical.
Specific learning goals are:
- Understanding the basic scaling relationships underlying drainage networks.
- Developing a quantitative framework for how rivers modify landscapes on long-timescales.
- To know how to generate a drainage network from topographic data including limitations
- Understand the range of materials transported in rivers and associated data
- Consider the importance of drainage network topology in analysing fluvial data
Specific sources given as citations within the slides and more general reading is in the final slide.
The slides for the Lectures are available by following the links below
| Date | Lecture | Instructor |
|---|---|---|
| 2021-11-29 9:00-10:00 Mon | Introduction to Rivers & Landscapes | Alex Lipp |
| 2021-12-02 14:00-15:00 Mon | Data from within rivers | Alex Lipp |
| Date | Exercise | Instructor |
|---|---|---|
| 2021-11-29 10:00-12:00 Mon | Extracting drainage from topography | Alex Lipp |
| 2021-12-02 15:00-17:00 Mon | Tracking pollution through drainage networks | Alex Lipp |
This module will deliver the core knowledge and skills required for accessing, loading, viewing and analysing 3D post-stack seismic reflection data which provides images of the Earth's subsurface for environmental and geotechnical engineering purposes. In order for you to be able to make use of these data as data scientists we need to cover some geological and geophysical background.
This week, we will focus on:
- The fundamentals of the seismic reflection method and how seismic reflection data is collected and processed
- The standard data format for seismic reflection data (SEG-Y), how to access it and use it for environmental and geotechnical purposes
- How data science and machine learning could revolutionise seismic studies
We won't be able to go through these topics in detail, but it is hoped that the material covered will give you enough information to inspire you as Environmental data scientists to the great potential of seismic data
- Key textbook for understanding the fundamentals of seismic reflection
Introduction to Geophysical Exploration, version 3. Kearey, Brooks and Hill. Oxford, John Wiley and Sons 2002 https://library-search.imperial.ac.uk/discovery/search?query=any,contains,introduction%20to%20geophysical%20exploration&tab=Everything&search_scope=MyInst_and_CI&sortby=date_d&vid=44IMP_INST:ICL_VU1&facet=frbrgroupid,include,9030987754194472865&offset=0
- Information on subsurface machine learning and seismic interpretation for data scientists https://agilescientific.com
Links to other useful articles and websites provided in the lecture slides
| Date | Lecture | Instructor | Moderator |
|---|---|---|---|
| 2021-11-30 9:00-12:00 Tue | Intro to seismic reflection data | Rebecca Bell | Raul Adriaensen |
| 2021-12-02 9:00-12:00 Thur | Intro to the SEG-Y data format and interpretation | Rebecca Bell | Raul Adriaensen |
| Date | Exercise | Instructor | Moderator |
|---|---|---|---|
| 2021-11-30 14:00-17:00 Tue | 1: Synthetic seismic models, 2: NMO corrections | Raul Adriaensen | Rebecca Bell |
| 2021-12-02 14:00-17:00 Thur | 3: Viewing SEG-Y data, 4: Seismic attributes | Raul Adriaensen | Rebecca Bell |
For facilitated setup it is recommended to create a virtual environment and install the required python packages. For anaconda environments an environemnt.yml file is provided, for setup run:
conda env create -f environment.yml
From within the base folder of the repository.
For other solutions a requirements file is provided, can be setup by running:
pip install -r requirements.txt
From the base directory.
Make sure to activate the environment after and run the notebooks from within this virtual environment! Lastly, make sure you have placed the memory intensive datafiles received via FileExchange under the data folder provided.
Assessment will be 100% by coursework. It is all open book. The assessment will involve 33% of the question on Landscapes and Drainage and 67% on Seismic reflection imaging Exercises will be distributed and submitted via GitHub Classroom on Friday. SEG-Y data will be downloaded from a File Exchange link to be sent at 1pm on Friday. Data for the landscapes assessment will be provided with the assessment notebook.
| Release Date | Due Date | Topic |
|---|---|---|
| 2021-12-03 Fri 13:00 | 2021-12-03 17:00 Fri | Landscapes and Seismic reflection imaging |