Application of Improved Gray Markov Dynamic Model in Predicting Corrosion Rates of Oil and Gas Pipelines

In order to improve the accuracy of the residual life prediction of buried pipelines, the traditional grey Markov prediction model was optimized. The corrosion rate of pipeline was regarded as a gray system, after smooth processing of the original data of the gray model, an unbiased gray model of iso-dimensional new information was established, and the macroscopic value of corrosion rate was predicted. Based on the residual of the predicted grey model predictive value, combined with the Markov chain model, the second smoothing process and whitening coefficient optimization were performed, and the residual correction value was obtained. Finally, a combination of two optimization models yielded a predicted value for the corrosion rate of the pipeline. The example test proved that the model could effectively overcome the shortcomings of long-term dynamic prediction of the system. Compared with the traditional grey Markov chain prediction model, the prediction accuracy was improved by 40.33%, and the prediction result had a higher degree of fitting with the measured value.