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Abstract
Chapter from: CA
3: Stochastic Modeling and Geostatistics
Edited by
Jeffrey M. Yarus and Richard L. ChambersAuthor:
Andres S. Hatloy Methodology and Concepts
Published 1994 as
part of Computer Applications 3
Copyright © 1994 The American Association of Petroleum
Geologists. All Rights Reserved. |
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Chapter 10
*
Numerical Facies
Modeling Combining Deterministic and Stochastic MethodsAndres S. Hatløy
Geomatic
Oslo, Norway
*
ABSTRACT
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. |
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