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The AAPG/Datapages Combined Publications Database
Journal of Petroleum Geology
Abstract
Journal of Petroleum Geology, vol.
COMBINING GEOSTATISTICS AND MULTI-ATTRIBUTE
TRANSFORMS: A CHANNEL SAND CASE STUDY,
BLACKFOOT OILFIELD (ALBERTA)
*Hampson-Russell Software Services Ltd, 510 715-5th Ave. SW, Calgary AB T2P 2X6, Canada.
**University of Calgary, Dept. of Geology and Geophysics, 2500 University Drive NW,
Calgary AB T2N 1N4, Canada.
Corresponding author: B. Russell <[email protected]>
In this paper, we combine the methods of geostatistics and multi-attribute
reservoir
parameter prediction (the multi-
attribute
transform) for the integration of
seismic
and
well log data, and illustrate this new procedure with a case study involving the prediction
of porosity at the Blackfoot oilfield, central Alberta. The objectives of the survey were to
delineate incised, valley-fill sediments within the Early Cretaceous Glauconitic Formation
at this field and to distinguish between sand-fill and shale-fill. The input consisted of
twelve porosity logs together with a 3D
seismic
volume and the inversion of this volume.
Although an excellent correlation was found between porosity and the initial inverted
acoustic impedance volume, the combination of traditional geostatistics and the multi-
attribute
transform produced an improved final result.
Our approach uses well logs to "train" the multi-attribute
transform algorithm. We
first extract average porosity values over the depth zone of interest, and compare these
values to average
seismic
attributes over the same zone. Cross-validation is used to show
which attributes are significant. We then apply the results of the training and cross-validation to data slices derived from both the
seismic
data cube and the inverted cube to
produce an initial porosity map. Finally, we improve the fit between the well-log values
and the porosity map using cokriging.
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