A classification is proposed, based mainly on major element analytical data plotted in a coherent set of three simple chemical-mineralogical diagrams. The procedure follows two complementary steps at two different levels. The first is concerned with the individual sample: the sample is given a name (e.g. granite, adamellite, granodiorite) and its chemical and mineralogical characteristics are determined. The second one is more important: it aims at defining the type of magmatic association (or series) to which the studied sample or group of samples belongs. Three main types of association are distinguished: cafemic (from source-material mainly or completely mantle-derived), aluminous (mainly or completely derived by anatexis of continental crust), and alumino-cafemic (intermediate between the other two types). Subtypes are then distinguished among the cafemic and alumino-cafemic associations: calc-alkaline (or granodioritic), subalkaline (or monzonitic), alkaline (and peralkaline), tholeiitic (or gabbroic-trondhjemitic), etc. In the same way, numerous subtypes and variants are also distinguished among the aluminous associations using a set of complementary criteria such as quartz content, colour index, alkali ratio, quartz–alkalies relationships and alumina index.Although involving a new approach using partly new criteria, this classification is consistent with most of the divisions used in previous typologies. The method may also be used in the classification of the volcanic equivalents of common plutonic rocks.
This classification is based on cationic calculations from major element data and then applied to simple chemical-mineralogical diagrams. The method follows two sequential steps. The first step is concerned with characterising the individual sample. From the cationic values, the sample is identified by name and its chemical and mineralogical characteristics are determined. The second and most important aim of the chemical-mineralogical diagrams is to define the magmatic association to which the sample or group of samples belong. Based on chemical data, this method can also be used to classify common volcanic rocks. Several applications are presented.
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