We propose to incorporate fault slip information into predictive painting to help it spread information across faults correctly. Three methods of processing the fault slip information have been presented, and the numerical tests have verified their effectiveness. We use the application of automatic horizon picking to test the proposed methods in the examples. Both the area partition and the fault-zone replacement methods are efficient and easy to implement. However, the former requires dividing the 2D section or 3D volume into small parts, which may be challenging for complicated fault structures, and the latter needs to select an appropriate fault zone width to avoid aliasing issues, which may be difficult for images with dense fault distributions. In these two cases, we suggest to use the more powerful unfaulting method. The unfaulting method can work well in complex faulting scenarios, such as horsts and grabens. When unfaulting the image with intersecting faults, it is necessary to move both fault blocks and faults themselves (Wu et al., 2016). Compared to the first two methods, unfaulting method has a much higher computational cost. A 3D extension of the three methods is straightforward, once the fault curves are replaced by fault hyper-surfaces.