This is the third and last post in our series on trained Machine Learning models developed by Lundin GeoLab that are released in OpendTect’s Machine Learning library. Two weeks ago, we presented SimpleHmult, a model to attenuate horizontal multiples. In last week’s post we showed an example of the application of Desmile, a model to remove migration smiles.

AJAX, an ML model to enhance the visual quality and interpretability of 3D seismic

Today, we present AJAX, a model trained to do a series of postprocessing steps in order to enhance the visual quality and interpretability of a seismic volume. This includes:

  • Frequency dependent structurally consistent noise attenuation
  • Bandwidth enhancement.

The model does not preserve amplitudes and frequency content of input volume. The slider shows a seismic section before and after application of AJAX (courtesy Lundin GeoLab).

For more information or to request a Machine Learning demo license, please email This email address is being protected from spambots. You need JavaScript enabled to view it..

The next post in this series of posts is available.