Application of Analytical Methods in Predicting Waterflood Performance of Reservoirs with Stochastic Sand Bodies

Due to the complex architecture of fluvial reservoirs composed of uncorrelatable (stochastic) sand bodies, straightforward application of simple one dimensional analytical methods to predict their waterflood performance is not possible. This is due to the inadequacy of the existing techniques to represent the complex connectivities between flow elements in one dimensional models. In this paper, a new stochastic sand modelling method is presented. It simplifies sand description in grid blocks for simulation, and for averaging of the reservoir parameters such as permeability and porosity. Although the method is conditioned by the available seismic and well data which are extremely sparse, it employs only modest use of statistical methods. Also, contrary to many current techniques which are restricted to two dimensional realisation, the current method extends the realisation into three dimensions. This is carried out by using the special stochastic sand conditioning technique in which the generated flow elements are matched to a prescribed girded domain.