--> ABSTRACT: Sedimentary Cycles on a Carbonate Platform Edge: Computer Model Test for Autocyclicity, by Andrew T. Fisher; #91043 (2011)

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Sedimentary Cycles on a Carbonate Platform Edge: Computer Model Test for Autocyclicity

Andrew T. Fisher

Meter-scale sedimentary cycles in shallow-water carbonate environments are geologically common and usually attributed to eustatic sea level fluctuations, local tectonic subsidence and isostatic adjustment, and/or climatic and associated runoff variations (allocycles) or system-dynamic controls (autocycles). I designed a computer model to simulate sedimentation on a shallow-water, carbonate-platform edge. The model approximates realistically coupled hydraulic, eustatic, tectonic, and biologic processes to simulate meter-scale bedding relationships, and prints isostatically balanced cross sections. Each 100-k.y. model run identifies eight separate sediment types and mixtures. Input parameters include initial platform shape and depth, initial deposition and erosion rates, an subsidence and sea level change rates. Cyclic sedimentation is induced through multiple combinations of fluctuating sea level and variable tectonic subsidence, and tests are performed in an attempt to induce autocycles (i.e., without fluctuating sea level) that leave a similar record.

After running the model with more than 200 different input parameter sets, the following is suggested: (1) the model predicts reef, sand-shoal, and mud-bank aggradation, erosion, and progradation at accepted rates; (2) model sediment-body shapes and relationships appear similar to those seen in the record and depicted by more qualitative models; (3) under conditions of fluctuating sea level, distinct, repeating, meter-scale sedimentary allocycles are generated; and (4) no such cycles can be modeled autocyclically.

The implication is that allocycles, not autocycles, can be produced in the model environment. Although more work is needed to make the model more realistic and robust, the insight it provides into sedimentation processes and dynamics makes it a highly useful predictive tool.

AAPG Search and Discovery Article #91043©1986 AAPG Annual Convention, Atlanta, Georgia, June 15-18, 1986.