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Modeling Natural Gas Reservoirs: David vs. Goliath

Authors: Richard Collier; Ellis Monash; Paul Hultquist;

Modeling Natural Gas Reservoirs: David vs. Goliath

Abstract

ABSTRACT For many years it has been standard practice to use very involved grid models to describe the reservoir behavior for the oil and gas industry. These grid models represent sizable investments in both time and money and are used in many instances in a sparing manner so that the cost of getting the needed reservoir information does not become prohibitive. In this paper we present an alternative model for a gas reservoir that is averaged over the geometry of the reservoir and hence represents a "zero-dimensional" model. It is called a "reservoir per se" model and describes the state variables as space averages through time. "David" is thought of as a small, efficient, low cost and low maintenance model that can be used as a simple alternative to, or prelude to, the use of the larger grid or "Goliath" type models. "Goliath" is pictured as big, bulky, not very efficient, high cost, high maintenance, and needing large amounts of input data. The particular "David" model — the reservoir per se model — that is presented does a good job in describing the bulk properties of the gas reservoir and has been validated in eighteen distinct cases. This model can and should be used when "simple" reservoir answers are needed quickly and at low computer cost.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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