Uncertainties in Static Reservoir Models
Beucher, Helene1, Didier Renard1, Brigitte Doligez2, Marco Pontiggia3, Giuseppe Bellentani3 (1) Ecole des mines de Paris, Fontainebleau, France (2) Institut Français du Pétrole, Paris (3) Eni, San Donato Milanese (Milano), Italy
The importance of uncertainties on the prediction of the recovered volumes and the fluid flow performance is well known. These uncertainties mainly come from the elaboration of the static reservoir model which results from the combination of the following steps.
The first task consists in building the architecture through the delineation of units. It must deal with the sparseness of the data control (few wells possibly deviated), the complexity of the stratigraphic description (number of homogeneous layers, presence of faults) and account for the seismic horizons available. Each layer is then populated with lithofacies reflecting the geological environment. This environment is characterized by the depositional sequence as well as the number of lithotypes (facies with similar properties), their proportions, trends and arrangement. Additional constraints on lithotype proportions are given by interpreted seismic attributes. Each lithotype is finally assigned some petrophysical properties. These variables are derived from various measurements types (core porosity, log porosity) and must be processed differently (averaging porosity while upscaling permeability). The hydrocarbon volumes are finally calculated above the oil water contact which governs the saturation law.
The purpose of this paper is to evaluate these sources of uncertainty through the study of an actual reservoir, performed in the geostatistical framework. These uncertainties are reproduced within a realistic layering model (multivariate method), using relevant stochastic techniques (pluri-gaussian, object based simulations) and choosing the adequate parameters (variogram, distribution, object intensity). The quantification is performed on global volumes as well as on local criteria (maps, connectivity index).