Seismic fault detection using marked point processes

A stochastic model for fault detection in 2D sections of seismic blocks is presented. The model is a marked point process in which each fault is modeled by a parabola. Three classical fault attributes are proposed to measure the likelihood of a fault. The computation of the likelihood can be based on one of the attributes as fault detector or on a composite function using the three measures. We present results on real 3D blocks to demonstrate the effectiveness of our approach. Using marked point process allows overcoming the drawbacks which are observed with the direct use of classical fault attributes.