Toy Occam inversion code for 1D MT (Magnetotellurics) method in Matlab

The example data are (literally) copied from Table 5 of the Constable 1987 paper, which is in turn from Cull (1985). See:

Constable, S. C., Parker, R. L., & Constable, C. G. (1987). Occam’s inversion: A practical algorithm for generating smooth models from electromagnetic sounding data. Geophysics, 52(3), 289–300.

Cull, J. P. (1985). Magnetotelluric soundings over a Precambrian contact in Australia. Geophys. J. Roy. Astr. Sot., 80, 661-675.

see also my toy occam code for DC resistivity:

[https://github.com/dong-hao/occam1ddc]

See example/testbench.m for a simple demonstration on how to load the data and call the inversion code.

This was one of many toy codes I fiddled with when I was a student - I hope this could be useful to our students nowadays in the EM community. Those who want to try this script are free to use it on academic/educational cases. But of course, I cannot guarantee the script to be working properly and calculating correctly (although I wish so). Have you any questions or suggestions, please feel free to contact me (but don't you expect that I will reply quickly!).

git clone https://github.com/dong-hao/occam1dmt/ your_local_folder

The internal scale here is log10(Ohmm) - instead of linear scale for both resistivity and apparent resistivity. The layer depth is in (linear) metres, while the impedance phase is in rads.

Currently the internal error here is standard deviation.

cd to_you_local_folder
git pull 

DONG Hao – [email protected]

China University of Geosciences, Beijing

Distributed under the GPL v3 license. See LICENSE for more information.

[https://github.com/dong-hao/occam1dmt]

Those who are willing to contribute are welcomed to try - but I probably won't have the time to review the commits frequently (not that I would expect there will be any).

1. Fork it (https://github.com/dong-hao/occam1dmt/fork)
2. Create your feature branch (git checkout -b feature/somename)
3. Commit your changes (git commit -am 'Add some features')
4. Push to the branch (git push origin feature/somename)
5. Create a new Pull Request - lather, rinse, repeat