Application of the deterministical and stochastical geostatistical methods in petrophysical modeling, case study Upper Pannonian reservoir, Sava Depression

Abstract

Deterministic methods are still widely used for reservoir characterization and modelling. The result of such methods is only one solution. It is clear that our knowledge about the subsurface is uncertain. Since stochastic methods include uncertainty in their calculations and offer more than one solution sometimes they are the best method to use. This paper shows testing of the deterministic (Ordinary Kriging) and stochastic (Sequential Gaussian Simulations) methods of reservoir properties distribution in the Lower Pontian hydrocarbon reservoirs of the Sava Depression. Reservoirs are gas- and oil-prone sandstones. Ten realizations were obtained by Sequential Gaussian Simulation, which are sufficient for defining locations with the highest uncertainties of distributed geological variables. The results obtained were acceptable and areas with the highest uncertainties were clearly observed on the maps. However, high differences of reservoir property values in neighbouring cells caused the numerical simulation duration to be too long. For this reason, Ordinary Kriging as a deterministic method was used for modelling the same reservoirs. Smooth transitions between neighbouring cells eliminated the simulation duration problems and Ordinary Kriging maps showed channel sandstone with transitional lithofacies in some reservoirs.