wavelet-based-inversion

Scale-dependent wavelet-based regularization scheme for geophysical 1D inversion

👉 Looking for a version in 2D or higher? Reach out or check out our more recent paper here!

This flexible inversion scheme allows to easily obtain blocky, smooth and intermediate inversion models. Different inversion models are obtained by simply changing the wavelet basis.

• db1: blocky inversion models
• db2-db4: sharper inversion models
• db5+: smoother inversion models

Daubechies (db) wavelets are ideal (see Deleersnyder et al, 2021), however, other wavelets can also be used. Simply run pywt.wavelist() to list the available options. The shape of the wavelet basis function (e.g., look here) is an indication of the type of minimum-structure the regularization method will promote.

Easy to use

• Fits within the modular SimPEG framework (see SimPEG website) (see examples)
• Fits within your own inversion codes (see examples with empymod)

Documentation

https://1d-wavelet-based-inversion.readthedocs.io/en/latest/

How to cite

The method:

Deleersnyder, W., Maveau, B., Hermans, T., & Dudal, D. (2021). Inversion of electromagnetic induction data using a novel wavelet-based and scale-dependent regularization term. Geophysical Journal International, 226(3), 1715-1729. DOI: https://doi.org/10.1093/gji/ggab182

Open Access version on ResearchGate

The code:

Wouter Deleersnyder, & Robin Thibaut. (2022). WouterDls/1D-wavelet-based-inversion: Wavelet-Based Inversion (0.1.0). Zenodo. https://doi.org/10.5281/zenodo.6552695

Questions?

Contact us on GitHub!

• Wouter Deleersnyder
• Robin Thibaut