History matching tutorial

Run in the cloud (no installation required)

• on Colab (requires Google login):
• on a NORCE server (not generally available):

OR: install

Use this option for development, or if you simply want faster computations (your typical laptop is 10x faster than Google's free offering).

Prerequisite: Python>=3.10

If you're an expert, setup a python environment however you like. Otherwise: Install Anaconda, then open the Anaconda terminal and run the following commands:

conda create --yes --name my-env python=3.10
conda activate my-env
python --version

Ensure the printed version is 3.10 or higher.
Keep using the same terminal for the commands below.

Install

• Download and unzip (or git clone) this repository (see the green button up top)
• Move the resulting folder wherever you like
• cd into the folder
• Install requirements:
  pip install -r path/to/requirements.txt

Launch

• Launch the "notebook server" by executing:
  jupyter-notebook
  This will open up a page in your web browser that is a file navigator.
• Click on HistoryMatch.ipynb.

Developer guide

For development, you probably want to install requirements-dev.txt.

Personally I prefer to develop mostly in the format of standard python script. Then, thanks to the jupytext extension, I can convert this (.py) to a notebook (.ipynb) simply by opening the file in Jupyter, and ensuring that the file > Jupytext menu has check marks on both "Pair with ipynb" and "Pair with light script".

If you use vim I suggest folding (rather than wrapping) the comment blocks (corresponding to markdown cells) using

:setlocal foldmethod=expr foldexpr=getline(v:lnum)=~'^\#\ ' fdl=0

Contributors

This work has been developed by Patrick N. Raanes, researcher at NORCE. The project has been funded by DIGIRES, a project sponsored by industry partners and the PETROMAKS2 programme of the Research Council of Norway.