Accurate prediction of petroleum reservoir performance requires reliable models of the often complex reservoir heterogeneity. Geostatistical simulation techniques generate multiple realizations of the reservoir model, all equally likely to be drawn. Traditional to geostatistics, geological continuity is represented through the variogram. The variogram is limited in describing complex geological structures as it measures correlation between rock properties at two locations only: it is a two-point statistic. Reservoir analogs such as outcrops can serve as training images depicting the interpreted geological structure. Due to scarcity of well data, the variogram models are often borrowed from such training sets. However, the same training images could be utilized to extract more complex information in the form of multiple-point statistics measuring the joint dependency between multiple locations. This paper compares a traditional variogram-based geostatistical model vs. a novel geostatistical method utilizing multiple-point statistics borrowed from training images. The comparison is made on the basis of flow performance for a typical North Sea reservoir. To obtain such comparison a 'true' reference reservoir is generated using object-based simulation that depicts the complex intertwining of fluvial channels. Next, a different but similar reservoir is generated, termed the 'training reservoir.' The latter is used to extract the necessary structural information, be it variograms or multiple-point statistics, to build multiple geostatistical models of the true reservoir conditioned to sparse well data. A waterflood flow scenario with an inverted five-spot pattern is simulated using ECLIPSE on the true reference and the various geostatistical models. Water breakthrough characteristics and water saturation distributions are used for comparison.
All Science Journal Classification (ASJC) codes
- Fuel Technology
- Energy Engineering and Power Technology