The full week: 5 days of instruction. The first 3 days covers the basics of scientific Python, from scratch. Day 4 introduces data management with Pandas and machine learning with scikit-learn. Day 5 is a less structured 'hack day' for personal projects: let us help you get started on your own project.
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These blog posts are drawn from some of the geocomputing course materials. Most of them have complete IPython Notebooks, so you can follow along in the code.
- To plot a wavelet — Evan shows how to make and plot a Ricker wavelet.
- To make a wedge — Evan shows how to make a simple wedge model.
- To make up microseismic — Evan looks at 3D plotting, and generating test data.
- Relentlessly practical — Matt introduces the SEG Tutorials series with an example.
- The Blangy equation — Matt reproduces the figures from a classic paper on AVO.
- How much rock was erupted from Mt St Helens? — Evan looks at maps.
- Slicing seismic arrays — Slicing is a fundamental concept in Python.
- Well tie calculus — Evan shows how to make a synthetic seismogram from scratch.
- The race for useful offsets — Evan models a CMP gather.
- Laying out a seismic survey — Evan shows how to model a simple seismic acquisition.
- It goes in the bin — collecting traces from a 3D survey, making fold maps, and spider plots.
- Seismic survey layout: from theory to practice — the effect of station gaps from local ground conditions.
- Making and Manipulating 2D colourmaps — co-rendering seismic attributes on time slices.
- Corendering more attributes — light-sources, bump-mapping, and opacity sculpting.