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Traditional facies models lack quantitative information concerning sedimentological features: this significantly limits their value as references for comparison and guides to interpretation and subsurface prediction. This paper aims to demonstrate how a relational-database methodology can be used to generate quantitative facies models for fluvial depositional systems. This approach is

Cite this article as: Na Yan, Nigel P. Mountney, Luca Colombera and Robert M. Dorrell, A 3D forward stratigraphic model of fluvial meander-bend evolution for prediction of point-bar lithofacies architecture, Computers and Geosciences, http://dx.doi.org/10.1016/j.cageo.2017.04.012 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

No abstract

Depositional (facies) models of fluvial architecture permit straightforward categorization of deposits, but are necessarily simplistic. Here we describe a complementary database methodology which is designed to encapsulate the inherent complexity of fluvial systems and their preserved deposits. The database is implemented as a series of tables (characterizing qualitative and quantitative architectural and geomorphological properties and system attributes) populated with data derived from peer-reviewed studies of both modern rivers and ancient fluvial successions, and from other reliable sources. Architectural properties (geometries, internal organization, spatial distribution and reciprocal relationships of lithosomes) are assigned to three different orders of genetic bodies organized in a hierarchical framework, ultimately belonging to stratigraphic volumes that are homogeneous in terms of their controlling factors and internal parameters. Interrogation of the database generates a varied suite of quantitative information, whose principal applications include: (i) the quantitative comparison of fluvial architecture to evaluate the relative importance of intrinsic and extrinsic controls; (ii) development of quantitatively justified fluvial depositional models through the integration of data from multiple sources; (iii) development of better constraints on the workflows used to infer borehole correlations and to condition stochastic models of subsurface architecture; (iv) identification of appropriate modern and ancient analogues for hydrocarbon reservoirs.