akuhara / RF_INV

Receiver function inversion by reversible-jump Markov-chain Monte Carlo

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Note

This software is no longer being updated. Please consider adopting our new software, SEIS_FILO (https://github.com/akuhara/SEIS_FILO), which offers enhanced features like joint inversion with dispersion curves.

RF_INV

Transdimensional inversion of receiver function waveforms by reversible-jump Markov-chain Monte Carlo

(c) 2018-2019 Takeshi Akuhara (Email: akuhara @ eri.u-tokyo.ac.jp)

Any bug report and suggestions are welcome!

Features

  • Applicable to OBS & borehole station
    • Model can include the sea water on its top. Also the station may be buried.
  • Multiple input traces
    • Can asign different ray parameter and Gaussian-filter for each trace.
  • Can use S receiver functions
    • Joint inversion of P and S receiver functions is also possible.
  • Parallel tempering
    • More efficient than conventional MCMC.
  • Invert for velocity perturbation
    • Non-uniqueness of inversion can be mitigated by constraint from a reference velocity model.

See Wiki for more details.

Terms of Use

  • Please clarify the URL of the GitHub repository (https://github.com/akuhara/RF_INV) and developer's name (Takeshi Akuhara) when you make any presentation or publish articles using this program.
  • This program is licensed under the GNU General Public License v3.0.

Requirements


Manual

A manual is available here.

About

Receiver function inversion by reversible-jump Markov-chain Monte Carlo

License:GNU General Public License v3.0


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Language:Fortran 85.2%Language:Python 13.0%Language:Makefile 1.7%