Delineation of thin conglomerate deposits using multicomponent seismic data

Brad D. Nazar and Don C. Lawton


This study involved the analysis of a multicomponent data set acquired in the Carrot Creek oilfield of west-central Alberta. One of the unique features of this data is the presence of a strong radial-component (P-SV) amplitude anomaly at the location of oil-producing conglomerate deposits. The vertical (P-P) component, comparatively, exhibits only a subtle amplitude variation at the same location.

The Cardium conglomerate in this area was found to have a P-wave velocity of 4327 m/s and a Poisson's Ratio between 0.18 and 0.22. Over- and underlying the conglomerate are thick shale deposits having P-wave velocities of 3920 and 4003 m/s respectively, and a Poisson's Ratio of 0.31.

AVO forward modeling, shows a polarity reversal with offset occurring on the vertical (P-P) but not the radial component, for the conglomerate event. It is this polarity reversal on the vertical component which causes the poor amplitude response at the location of the Cardium conglomerate. Upon stacking, the near- and far-offsets of the vertical component add destructively whereas the radial-component offsets add constructively, thus causing the Cardium conglomerate to be more easily seen on the radial component section.

The P-P and P-SV data were found to be most sensitive to variation in conglomerate thickness over the 0-1000 m and 500-2000 m offset-ranges, respectively. From this result it was found that better imaging of the Cardium conglomerate could be achieved by either limiting the offset-range during acquisition or by generating offset-range stacks.

It was also found that by using both the P-P and P-SV data, estimates for Poisson's Ratio for specific seismic intervals could also be calculated. This interval analysis was in turn capable of identifying variations in conglomerate thickness by the presence of lows in the calculated Poisson's Ratios. Two such lows could be identified using the multicomponent data, which in turn correlate well with the location of the conglomerate deposits.

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