  In the field of seismic interpretation, univariate databased maps are
commonly used by interpreters, especially for fault detection. In these maps,
contrast between target regions and the background is one of the main factors
that affect the accuracy of the interpretation. Since univariate data-based
maps are not capable of providing a high contrast representation, to overcome
this issue, we turn these univariate data-based maps into multivariate
data-based representations using color blending. We blend neighboring time
sections, frames that are viewed in the time direction of migrated seismic
volumes, as if they corresponded to the red, green, and blue channels of a
color image. Furthermore, we apply color transformations to extract more
reliable structural information. Experimental results show that the proposed
method improves the accuracy of fault detection by limiting the average
distance between detected fault lines and the ground truth into one pixel.
