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Comparison of Deterministic and Stochastic Previous HitFaultNext Hit Seal Techniques

Stephen J. Dee, Graham Yielding, Brett Freeman, and Peter Bretan
Badley Geoscience Limited, Hundleby, Lincolnshire, United Kingdom

Published Previous HitfaultNext Hit seal studies are, either, deterministic based on a static model of the reservoir geometry, or stochastic where the reservoir geometry is unknown or uncertain.

In a deterministic model, prediction of the locations of reservoir overlaps is made from the static model of the reservoir horizon and Previous HitfaultNext Hit geometry. The principal aim is to map faulted reservoir overlaps and determine their sealing character. This is usually performed using a predictive algorithm such as the shale gouge ratio (SGR, Yielding et al. 1997) that relates the shale content of the faulted formations to the sealing capacity of the Previous HitfaultNext Hit rock.

Deterministic Previous HitfaultNext Hit seal studies are sensitive to the uncertainties associated with mapping of horizons in proximity to faults and inherent uncertainty in the static Previous HitfaultNext Hit Previous HitinterpretationNext Hit in both position and Previous HitfaultNext Hit zone complexity. Uncertainty in the static structure model can be addressed by convolving uncertainty in throw magnitude with juxtapositions at the Previous HitfaultNext Hit. This does not address the uncertainty in the distribution of reservoirs on either side of the Previous HitfaultNext Hit. Stochastic models offer the possibility to test multiple realisations of the Previous HitstratigraphicNext Hit stacking geometries (Fairchild et al. 2004) capturing the uncertainty in the position of the reservoir at the Previous HitfaultNext Hit. The principal assumption is that these stacked reservoir zones are laterally continuous covering the entire likely fill area.

Do these conceptually different approaches lead to different predictions of Previous HitfaultTop seal? Comparison of the predictions between the two methods, using published case studies, shows a surprising degree of conformity.