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Global cyclostratigraphy: a model of carbonate growth patterns
Authors:YY Li  I Lerche  MA Perlmutter
Abstract:Cyclostratigraphy is the study of cyclic depositional patterns produced by climatic and tectonic processes. A global-scale quantitative cyclostratigraphic model is described which simulates carbonate growth patterns controlled by tectonic and climatic processes. The model uses seven factors simulating the effects of physical and chemical environments on the deposition rates of carbonate accumulations. These factors are sea-level change, the rate of basement subsidence, food supply (influence of nutrients), available sunlight, temperature, salinity and dissolved oxygen. The factors are considered as functions of climatic and tectonic processes. The model also integrates Milankovitch-induced short-term climatic changes with the long-term tectonic evolution of basins to examine the potential carbonate accumulation patterns. The two-dimensional computer model results provided here show that: (1) carbonate growth patterns in different climates and under different tectonic processes can be modelled quantitatively; (2) carbonate production increases towards the equator (decreasing latitude) as the temperature and nutrition supply increase in tropical belts, and production changes because of expansion or contraction of the tropical belt in different climatic periods; (3) when matched with the turbidity, the model describes different carbonate accumulation patterns in different climatic patterns; (4) at either abnormally high or low salinity, carbonate accumulation rates decline sharply, and the salinity becomes normal away from the strand line; and (5) cyclic sea-level changes cause a cyclic change of carbonate accumulation. A case study is presented from the Upper Pennsylvanian of Texas. The simulation results indicate that carbonate growth patterns observed from field, well or seismic data are accurately modelled by the quantitative procedure given here.
Keywords:global cyclostratigraphy  carbonate growth patterns  two-dimensional modelling
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