Inorganic silicification of ancient carbonate rocks

Article Type

Research Article

Publication Title

Journal of Sedimentary Research


Mechanisms of inorganic silicification of early Precambrian (older than 750 Ma) carbonate rocks remain equivocal. A quantitative model is presented here that captures the essence of ancient inorganic silicification of the carbonate rocks and is based on the hypotheses that carbonate silicification, a volume-conservative replacive process, is driven by crystallization stress induced by the growth of the guest mineral. Results of the quantitative model for silicification of calcitic limestone and dolostone are compared and validated against available independent observations and are found to be geologically reasonable. The quantitative model suggests that silicification of carbonate rocks is dependent on the host-rock composition and that calcitic limestones will be readily silicified compared to dolostone and/or aragonitic limestone. Results also show that silicification rate of carbonate rocks- irrespective of their composition-increases with increase in silica supersaturation and reactive surface area. Porosity and permeability of the host rock also increases the silicification rate of the carbonate rocks. Results also predict that substantial volume of silica-saturated fluids is required for inorganic silicification of a one-meter cube of carbonate rock. The quantitative model presented here has its limitations and should not be viewed as a unique and truly realistic representation of the carbonate silicification mechanism. The quantitative model presented here is unable to explain the formation of porosity and subsequent volume reduction of the parent material during the replacement process as observed in replacement experiments. Also, the effect of pH on silicification of carbonate rocks cannot be quantitatively estimated in this study. The quantitative model presented here should be viewed as one of the possible mechanisms of carbonate silicification that has to be tested further with experimental data and by model refinement.

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