An underground early warning method based on a hidden Markov model

The invention discloses an underground early warning method based on a hidden Markov model. The underground early warning method comprises the following steps: S1, obtaining initial sample data; S2, predicting data of a next time period; S3, selecting real data and bringing the real data into an accident candidate set; S4, acquiring a real accident state corresponding to the real data in each timeperiod; S5, obtaining a real accident state sequence corresponding to the initial sample data; S6, establishing an initial early warning model by adopting the hidden Markov model, and training the initial early warning model to obtain a trained early warning model; And S7, obtaining data generated by the target drilling well in real time, taking the data as input of a post-training early warningmodel, and carrying out real-time early warning through the post-training early warning model. According to the method, the comprehensiveness of underground prediction can be effectively improved, sothat the prediction result