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Cutting identification is one of the most important links in the course of cutting logging which is very significant in the process of oil drilling. In the present paper, LIBS was used for identification of four kinds of cutting samples coming from logging field, and then multivariate analysis was used in data processing. The whole spectra model and the feature model were built for cuttings identification using PLS-DA method. The accuracy of the whole spectra model was 88.3%, a little more than the feature model with an accuracy of 86.7%. While in the aspect of data size, the variables were decreased from 24,041 to 27 by feature extraction, which increased the efficiency of data processing observably. The obtained results demonstrate that LIBS combined with chemometrics method could be developed as a rapid and valid approach to cutting identification and has great potential to be used in logging field.