Quantification of granite textures and structures using a mathematical model for characterization of granites has been a long-term attempt of mathematical geologists over the past four decades. It is usually difficult to determine the influence of magma properties on mineral crystallization forming fined-grained granites due to its irregular and fine-grained textures. The ideal granite model was originally developed for modeling mineral sequences from first and second-order Markov properties. This paper proposes a new model for quantifying scale invariance properties of mineral clusters and voids observed within mineral sequences. Sequences of the minerals plagioclase, quartz and orthoclase observed under the microscope for 104 aplite samples collected from the Meech Lake area, Gatineau Park, Québec were used for validation of the model. The results show that the multi-scale approaches proposed in this paper may enable quantification of the nature of the randomness of mineral grain distributions. This, in turn, may be related to original properties of the magma
