Impact on Gross-Rock Volume Distributions from Uncertainties in Surfaces and Hydrocarbon Contacts

The gross-rock volume often accounts for the largest uncertainty in reserves. It is therefore important to obtain a correct gross-rock volume distribution and to reduce the uncertainty by using all available data. We demonstrate a way of obtaining accurate volume estimates by imposing realistic and consistent physical and stochastic relationships between the surfaces and hydrocarbon contacts that define the reservoir rock volume. The uncertainty is reduced by using all relevant information collected in wells; well markers, zone logs in horizontal sections, and gas/fluid content along wells. Uncertainties in all these data types are handled. The impact on volume distributions from different assumptions and data types are demonstrated by several examples. We will in particular demonstrate how restrictions on the possible spill point depth have impact on the potential trap size and the trapped volume. Some of the results are obtained using standard stochastic simulation (Monte Carlo) techniques but in particular the highly non-linear relationship between a surface and its spill point requires rejection sampling techniques. Rejection sampling is simple but very inefficient so a fast approximate approach to simulating surfaces is investigated. The conclusion is that the approximation works for calculating volumes but individual surface realizations have unacceptable artefacts.