Interpretation of uncertain data is the basis for understanding many Earth processes; in particular, uncertain data underpin much of the world's hydrocarbon exploration and future carbon minimization strategies (CO2 storage and radioactive waste disposal). It is therefore crucial to develop techniques and protocols that will improve geoscientists’ interpretational accuracy. We asked 184 academic and industry experts to interpret a typical oil-industry synthetic seismic reflection data set and found that just over one-third got the “right” answer. Using multivariate analyses we show that interpretational accuracy is significantly improved for experts educated to the level of a Master's degree and/or doctorate (Ph.D.) (regardless of years of experience). Furthermore, although only 18 of 184 experts validated their interpretation by checking geometric and evolutionary feasibility, these experts were almost three times more likely to produce the correct result than those that did not. These results would not have been apparent from traditional detailed expert elicitation studies, as their sample sizes are too small. Our findings strongly suggest that significant improvements in the reliability of interpretations of inherently uncertain geological data sets could be made by increasing the proportion of people recruited into industry and academia who have a Master's or Ph.D. degree, and by changes to industry workflows and quality assurance procedures to explicitly include validation techniques.