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The AAPG/Datapages Combined Publications Database

AAPG Bulletin


AAPG Bulletin, V. 103, No. 2 (February 2019), P. 433-467.

Copyright ©2019. The American Association of Petroleum Geologists. All rights reserved.

DOI: 10.1306/07031817054

Statistical analysis of forward stratigraphic models in complex salt provinces: The central Scotian Basin case study

N. Hawie,1 E. Marfisi,2 F. Saint-Ange,3 and A. W. A. MacDonald4

1Division of Global Solutions, Beicip-Franlab, Paris, France; [email protected]
2Division of Global Solutions, Beicip-Franlab, Paris, France; [email protected]
3Division of Global Solutions, Beicip-Franlab, Paris, France; [email protected]
4Nova Scotia Department of Energy, Halifax, Nova Scotia Canada; [email protected]


Predicting vertical and lateral facies variations in various depositional environments remains a major challenge in the oil and gas industry because it impacts petroleum system assessments and the associated exploration-risking phase. The use of multidisciplinary constraints (geomorphology, geology, geophysics) in forward stratigraphic models sheds light on the complex interaction of local, regional, and global driving mechanisms that influence sediment transport and deposition along continuously evolving landscapes. In this paper, we develop an integrated statistical approach to examine the sensitivity of forward stratigraphic models in complex salt provinces to several parameters, including water discharge, sedimentary load, grain size and associated diffusion coefficients, and slope. This statistical analysis was applied to the Barremian–Albian sequence of the central Scotian Basin (Canada) and highlights the influence of complex salt kinematics on sediment pathway diversion and accumulation around salt domes and canopies. Forward stratigraphic modeling results point to regions of higher probability of Lower Cretaceous sandy reservoirs. Automating simulation runs significantly reduced the time required to achieve a statistically valid number of simulations and allowed the sensitivity of the model to be evaluated.

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