Inverse problems lie at the core of many geoscientific problems. By leveraging the concept of matrix-free linear operators, PyLops allows solving computationally intensive inverse problems with high-level code that is highly readable and resembles the underlying mathematical formulation.
In this tutorial participants will familiarize with the basic concepts of inverse problems, their numerical solution in the Python programming language, and the usage of PyLops in a variety of geophysical problems of increasing complexity, including an example of post-stack inversion of the Volve dataset. Basic knowledge of Python is required to be able to follow the tutorial and use the high-level API of PyLops.
Material for tutorial Matrix-free inverse problems with PyLops, to be taught at Transform 2021.
The material covered during the tutorial is composed of 3 jupyter notebooks. Participants can either use:
- local Python installation (follow these instructions to setup your environment)
- a Cloud-hosted environment such as binder or Google Colab (use links provided below to open the notebook directly in Colab).
Instructor¶
- Matteo Ravasi (mrava87), KAUST
Notebooks¶
Session | Exercise (Github) | Exercise (Colab) | Executed |
|---|---|---|---|
1: Introduction | |||
2: Horizon filling | |||
3: Post-stack inversion |
License¶
The material in this tutorial is open and can be modified and redistributed according to the chosen licenses.
- Text is licensed under CC BY Creative Commons License.
- Code is licensed under the Apache License, Version 2.0.