An Approach towards Automated Fault Interpretations in Seismic Data

In this paper, we present a methodology for interpreting faults from three dimensional seismic data. Faults are individual fractures across which there are visible offsets of horizons (or rock layers). 3D seismic data images of subsurface structure generated by reflecting seismic waves off rock layers have been used for hypothesizing subsurface structures. Since interpretation of seismic data is a highly time-consuming task, automated tools to assist the interpretation are crucial. Our work focuses on automating the correlation of horizons across a fault so that helping in defining the fault’s geometry. The correlation is made by integrating empirical structural geological models into normalized cross-correlation. We employ a multi-resolution approach defined on perceptual scale. Though still detailed evaluations are required, the results show correct matches. In areas of weaker signals, or where the seismic data are less clear, the results are incorrect correlations.