Summary
Reservoir-modeling practice has developed into a complex set of numerical
algorithms and recipes for modeling subsurface geology and fluid flow. Within
these workflows, a number of myths have sometimes been propagated, especially
in relation to (a) methods for handling net-to-gross (N/G), (b) implementation
of upscaling methods, and (c) conditioning of reservoir models to well data.
This paper discusses different practices in the use and upscaling of reservoir
data and models, by comparing two end-member approaches: (1) the N/G method and
(2) total-property modeling. Total property modeling, in which all rock
elements are represented explicitly, is the generally preferred method. The N/G
method involves a simplified representation of reality, which may be an
acceptable approximation. Implications for upscaling and conditioning reservoir
models to well data are discussed, and recommended practices are suggested.
Introduction
A number of weak assumptions have propagated within the oil industry and
related research groups with respect to how reservoir data are rescaled and
handled within the reservoir model. Three myths prevalent in reservoir modeling
are that
1. The net-to-gross (N/G) ratio is a trivial
concept.
2. Upscaling is not usually necessary.
3. Measurements at the well are fixed data
points.
While it is generally appreciated that the N/G ratio is an important
concept, it is widely and falsely assumed that treatment of N/G ratios in the
reservoir model is a trivial matter. Similarly, while the upscaling of flow
properties is an important research activity, a common assumption in practice
is that upscaling is a specialist research topic that does not significantly
affect practical reservoir modeling or, indeed, that other uncertainties
dominate over any upscaling uncertainties. Furthermore, although upscaling
methods are employed increasingly, too often standard recipes are used without
checking the validity of assumptions. The third myth is prevalent in the use of
common modeling techniques in which the focus is on geostatistical modeling of
the interwell volume with the assumption that the statistical variables must
merely be "tied to" or conditioned to (hard) well-data control points.
While it is generally true that interwell uncertainties are large compared to
well data, the well data sets them
selves have significant uncertainties in interpretation and rescaling,
especially for thin-bedded reservoir systems. This paper examines these issues
and suggests an improved practice for representation and transformation of
multiscale reservoir data in the reservoir model. Contrasting approaches to the
handling of N/G ratios and cutoff values are the main concern, but implications
for upscaling, handling of well data, and reservoir modeling are also
identified. The main goal is assumed to be reservoir modeling for flow
simulation and reservoir forecasting, but the arguments are also relevant for
volume and reserves estimation.
© 2008. Society of Petroleum Engineers
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History
- Original manuscript received:
18 February 2007
- Meeting paper published:
1 November 2007
- Revised manuscript received:
12 February 2008
- Manuscript approved:
9 March 2008
- Version of record:
25 October 2008
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