Published 1994 as part of Computer Applications 3
Copyright © 1994 The American Association of Petroleum Geologists.  All Rights Reserved.

In the North Sea only a small number of wells can be economically justified before important and often irreversible reservoir development decisions are made. The incorrect production forecasts the oil industry experienced during the 1970s and 1980s to a large extent likely were due to the use of oversimplified (i.e., too homogeneous) reservoir models. It became evident that detailed reservoir descriptions incorporating different types of heterogeneities were needed to quantify the uncertainty and, possibly, reduce the economic risk.

Heterogeneities exist on all scales from cementation of pores to displacement of fault blocks and must be accounted for, in one way or another, when generating a detailed reservoir description. Reservoir modeling is often divided into four steps to reflect the different scales of heterogeneity. The first step is to build the structural framework of the reservoir. The second step is to model the facies architecture and the distribution of the different facies types. The third step is to describe the petrophysical properties, and the fourth step is homogenization and scale-up to generate a model that can be applied in fluid flow simulations.

This paper focuses on numerical facies modeling and describes the SESIMIRA concept, which is an object-based method; however, the SESIMIRA approach is general and enables the user to combine deterministic and stochastic parameters. A case study demonstrates how a fluvial sequence has been modeled using a combination of empirical relations, probability distributions, and (geo)logical rules. The result is a set of realizations of the model in a computer format that can be used as input to petrophysical property modeling, reservoir communication studies, and fluid-flow simulations.

SESIMIRA has, during the last six years, been used with success to model different reservoir types. These models have been used to quantify the uncertainty in the facies architecture, as a basis for detailed models of petrophysical parameters, and to quality check sedimentological interpretations.