Stochastic Signal Processing

Seismic signal processing can be summarized in three main steps:

The classical approach to seismic processing is called deterministic processing because it relies on the application of deterministic geophysical laws to the processing of recorded seismic on shore or offshore acquisitions.

Stochastic signal processing offers a consistent mathematic framework (a probability model) to optimize the parameterization of geophysical laws involved in the processing and at the same time provide a quantification of the reliability of the processing (uncertainty management).

Some critical steps of deterministic processing have been translated into their stochastic counter parts such as: Quality control, Filtering, Wave separation, stacking, time depth conversion or volumetrics computations, others are underway such as: tomography, migration, velocity modelling and inversion.

In the session, we give the fundamentals on building probability models, on operating Stochastic Signal Processing, and we show how Probability Models are used in seismic processing:

The Theory of regionalized variables
Probability models
Variograms
Kriging
Simulations
Spatial Data Quality Assessment
Spatial Data Conditioning
Stochastic wave separation
Stochastic stack
Depth conversion

Special thanks to Luc Sandjivy and Arben Shtuka for their advice and invaluable help in creating these lessons and in providing the field data. The different data set have been processed thanks to UDOMORE software (http://www.seisquare.com/)