Prediction of Shale Plugs between Wells in Heavy Oil Sands using Seismic Attributes |
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| Authors: | F David Gray Paul F Anderson Jay A Gunderson |
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| Institution: | (1) Veritas DGC, Inc., 2200, 715 5th Ave. SW, Calgary, AB, Canada;(2) Apache Canada Ltd., Calgary, AB, Canada |
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| Abstract: | A fundamental geologic problem in the Steam-Assisted Gravity Drainage (SAGD) heavy oil developments in the McMurray Formation
of Northern Alberta is to determine the location of shales in the reservoirs that may interfere with the steaming or recovery
process. Petrophysical analysis shows that a key acoustic indicator of the presence of shale is bulk density. In theory, density
can be derived from seismic data using Amplitude Versus Offset (AVO) analysis of conventional or multicomponent seismic data,
but this is not widely accepted in practice. However, with billions of dollars slated for SAGD developments in the upcoming
years, this technology warrants further investigation. In addition, many attributes can be investigated using modern tools
like neural networks; so, the density extracted from seismic using AVO can be compared and combined with more conventional
attributes in solving this problem. Density AVO attributes are extracted and correlated with “density synthetics” created
from the logs just as the seismic stack correlates to conventional synthetics. However, multiattribute tests show that more
than density is required to best predict the volume proportion of shale (Vsh). Vsh estimates are generated by passing seismic
attributes derived from conventional PP, and multicomponent PS seismic, AVO and inversion from an arbitrary line following
the pilot SAGD wells through a neural network. This estimate shows good correlation to shale proportions estimated from core.
The results have encouraged the application of the method to the entire 3D. |
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| Keywords: | Amplitude vesus offset (AVO) case history interpretation inversion multicomponent |
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