In hydrocarbon exploration there are the things we know, things we know we don’t know and those things we don’t know we don’t know. This relates to the confidence one has in the understanding of the subsurface and can be based on data as well as models or analogues. This understanding can allow an exploration geologist to indicate whether or not imperative geological factors are in place that would allow a successful hydrocarbon accumulation to be present. For example, in area A one might be largely confident that all geological factors are in place (all geological chance factors are high) and this area would have low geological risk for finding oil. In area B one might be largely confident that one of the geological factors is not in place (one geological chance factor is low) making this an area of high geological risk for finding oil. However, in area C one might have absolutely no clue (confidence is zero) on weather a certain geological factor is in place, but this not necessary makes this area has higher geological risk than area B. In area C it will basically be a coin toss whether or not the imperative geological factor is in place, while in area B the certainty of it not being in place was already high. An appropriate approach for area C would probably be to acquire new data or re-assess old data and models to find clues on whether the needed geological factor is or isn’t in place. This is often referred to as “de-risking” but, to reduce confusion, could better be referred to as “increasing confidence” as the outcome of the study does not directly decrease the risk for finding oil. Possibly the new data indicates, with large confidence, that the imperative geological factor is not or only partially in place, and while this reduced the risk of making a wrong operational decision, it increases the geological risk for finding oil in the area. As this example indicates, probability factors, confidence and risk can be confusing concepts and clear definitions need to