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The Ardross Reservoir Gridblock Analog: Sedimentology, Statistical Representivity, and Flow Upscaling

By
Philip Ringrose
Philip Ringrose
Heriot-Watt UniversityEdinburgh, Scotland, U.K.
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Gillian Pickup
Gillian Pickup
Heriot-Watt UniversityEdinburgh, Scotland, U.K.
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Jerry Jensen
Jerry Jensen
Heriot-Watt UniversityEdinburgh, Scotland, U.K.
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Margaret Forrester
Margaret Forrester
Heriot-Watt UniversityEdinburgh, Scotland, U.K.
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Published:
January 01, 1999

Abstract

We have used a reservoir gridblock-size outcrop (10 × 100 m) of fluvio- deltaic sandstones to evaluate the importance of internal heterogeneity for a hypothetical waterflood displacement process. Using a dataset based on probe permeameter measurements taken from two vertical transects representing “wells” (5 cm sampling) and one “core” sample (exhaustive 2-mm-spaced sampling), we evaluate the permeability variability at different lengthscales, the correlation characteristics (structure of the variogram function), and importance of volume and data support. We then relate these statistical measures to the sedimentology.

We show how the sediment architecture influences the effective tensor permeability at the lamina and bed scales, and then calculate the effective relative permeability functions for a waterflood. We compare the degree of oil recovery from the formation: (1) using averaged borehole data and no geological structure, and (2) modeling the sediment architecture of the interwell volume using mixed stochastic/deterministic methods.

We find that the sediment architecture has an important effect on flow performance, mainly due to bed-scale capillary trapping and a consequent reduction in the effective oil mobility. The predicted oil recovery differs by 18% when these small-scale effects are included in the model. Traditional reservoir engineering methods using average permeability values only prove acceptable in high-permeability and low-heterogeneity zones. The main outstanding challenge, represented by this illustration of sub-gridblock scale heterogeneity, is how to capture the relevant geological structure along with the inherent geo-statistical variability. An approach to this problem is proposed.

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Contents

AAPG Memoir

Reservoir Characterization—Recent Advances

Richard A. Schatzinger
Richard A. Schatzinger
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John F. Jordan
John F. Jordan
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American Association of Petroleum Geologists
Volume
71
ISBN electronic:
9781629810720
Publication date:
January 01, 1999

GeoRef

References

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