Classification and Recognition of Polyhalite in Chuanzhong Based on Support Vector Machine

Polyhalite is mainly solid mineral potassium in Sichuan Basin, The most of polyhalite layer in Sichuan region is impurity, and usually accompanied by layers of gypsum, anhydrite, rock salt, and even deposited in the same layer. Conventional logging interpretation method can only roughly identificate polyhalite layers. Based on the theory of Support Vector Machine and logging interpretation methods,this paper creates prediction model with the input of logging curves, and discriminates the polyhalite reservoirs in the lower-middle Triassic strata. Compared with logging data, the accuracy rate of the discrimination results reaches 90%. According to the prediction model, identification model can be established with the curve features of polyhalite to discriminate pure polyhalite reservoirs, gypsiferous polyhalite reservoirs and polyhalite-gypsum reservoirs, the accuracy rate is 91.78%. The study demonstrates that Support Vector Machine is superior to the method of logging interpretation, and it has broad prospects in potash exploration.