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Quantitative Empirical Relationships for the Prediction of Subsurface Fluvial Sedimentary Architecture

Colombera, Luca; Mountney, Nigel; McCaffrey, William D.

Realistic prediction of fluvial reservoir geometries and connectivity requires a quantitative description of the sedimentary architecture of potential analogs on which to base deterministic and stochastic reservoir models. To tackle this issue, we propose a novel and innovative database approach to determining quantitative empirical relationships between sedimentary architecture and the boundary conditions that controlled deposition and also between the resultant architectural properties.

Quantitative descriptors are derived by analyzing the sedimentary architecture of many case studies within a database that stores multi-scale information from both ancient and modern depositional systems, together with information on system parameters (e.g. channel pattern) and controls (e.g. subsidence rate). Thus the database permits derivation of quantitative relationships describing the degree of association of different architectural properties; in reservoir-modeling workflows, for example, database-derived descriptive statistics of channel-sandbody dimensions expressed as a function of basin-wide channel-deposit proportions can be used in conjunction with borehole-derived channel-deposit proportions as forecasting tools. The ability to consider lithological heterogeneity at several scales enables external geometries to be linked to internal organization, thereby allowing derivation of quantitative descriptions of geometries related to facies assemblages defined to match known subsurface lithofacies associations.

The database can also be employed to derive empirical relationships between system controls or parameters and architectural properties. Such relationships can be referred to whenever knowledge on the boundary conditions governing the subsurface depositional system is available; for example, vertical channel-sandbody connectivity can be quantified as a function of system aggradation rate, or sandbody geometric parameters can be expressed as functions of the system drainage pattern.

Architectural relationships can be customized to best match the subsurface system being modeled by filtering the knowledge-base to include only data from case studies considered to be appropriate analogs, either in terms of sedimentary architecture or boundary conditions, or both.

Preliminary results demonstrate shortcomings in some qualitative relationships implied by physical stratigraphic models commonly used as predictive tools for subsurface fluvial architecture.


AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013