Due to an expected increase in geological voxel model data-flow and user demands, the development of improved quality control for such models is crucial. This study explores the potential of a new type of quality control that improves the detection of errors by just using gaze behavior of 12 geological experts. Gaze is used as input for an attention model that results in 'attended areas' on sliced representations of part of a geological voxel model. We compared attended areas to errors as manually marked by the experts. We found a clear match between manually marked errors and attended areas as determined using gaze. We also found that a large proportion of this match is reached within a small amount of total viewing time.