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Book Chapter

Extracting Maximum Petrophysical and Geological Information from a Limited Reservoir Database

By
Maqsood Ali
Maqsood Ali
Schlumberger-GeoQuestDenver, Colorado, U.S.A.
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Adwait Chawathé
Adwait Chawathé
Chevron Research Tech CompanyLa Habra, California, U.S.A.
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Ahmed Ouenes
Ahmed Ouenes
Reservoir Characterization Research and ConsultingDenver, Colorado, U.S.A.
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Martha Cather
Martha Cather
New Mexico Petroleum Recovery Research CenterSocorro, New Mexico, U.S.A.
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William Weiss
William Weiss
New Mexico Petroleum Recovery Research CenterSocorro, New Mexico, U.S.A.
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Published:
January 01, 1999

Abstract

The characterization of old fields lacking sufficient core and log data is a challenging task. This paper describes a methodology that uses both new and conventional tools to build a reliable reservoir model for the Sulimar Queen field. At the fine scale, permeability measured on a fine grid with a minipermeameter was used in conjunction with the pétrographie data collected on multiple thin sections. The use of regression analysis and a newly developed fuzzy logic algorithm led to the identification of key pétrographie elements that control permeability. At the log scale, old gamma ray logs were first rescaled/calibrated throughout the entire field for consistency and reliability using only four modern logs. Using data from one cored well and the rescaled gamma ray logs, correlations among core porosity, permeability, total water content, and gamma ray were developed to complete the small-scale characterization. At the reservoir scale, outcrop data and the rescaled gamma logs were used to define the reservoir structure over an area of 10 mi2 (26 km2) where only 36 wells were available. Given the structure, the rescaled gamma ray logs were used to build the reservoir volume by identifying the flow units and their continuity. Finally, history-matching results constrained to the primary production were used to estimate the dynamic reservoir properties, such as relative permeabilities, to complete the characterization. The obtained reservoir model was tested by forecasting the waterflood performance and was in good agreement with the actual performance.

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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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