The FISSSA module (developed by the RING Team in collaboration with IECL lab) provides functionalities to interpret fault networks stochastically from two dimensional seismic images. Fault description is formulated in terms of an explicit mathematical a priori model thanks to a marked point process model managing interactions between fault segments. This model is conditioned to data through a fault likelihood attribute thanks to a Gibbs probability distribution.

The proposed model to interpret faults is an adaptation of the Candy model. Another aspect is to test if the constructed model is able to generate patterns that are consistent with the input seismic data, using distance based methods, such as non parametric measures. These non parametric measures, which include the empty space, the nearest neighbor distance and the bivariate J functions are used to estimate how far the proposed model (Candy model) deviates from a purely random point process in terms of the output realizations.

The code uses the RINGPointProcess C++ library. It is avalable on Github and in the RING trainings page 

Contacts

• Fabrice Taty-Moukati
• Guillaume Caumon
• Radu Stoica

Related publications:

• Two dimensional seismic fault network interpretation using marked point processes
• From fault likelihood to fault networks: stochastic seismic interpretation through a marked point process with interactions