Drilling Overflow Diagnosis Based on the Fusion of Physical and Intelligent Algorithms

The diagnosis of overflow risk has always been an important area of research in drilling operations in the field of oil and gas engineering. In the face of the limitations and lag of traditional overflow diagnosis methods, the practical application effect of existing models and methods is not obvious, and there is no integration of the physical model and the intelligent algorithm model for overflow diagnosis, this paper proposes a method of adaptive weight fusion of physical model and intelligent algorithm model diagnosis results. Based on the fusion of the physical model and the intelligent algorithm model, an overflow diagnosis model of managed pressure drilling is established. The research results show that the fusion model in this paper can combine the accuracy weight of the physical model and the intelligent algorithm model for the intelligent diagnosis of overflow risk, which improves the mechanization and interpretability of the model and diagnosis results while ensuring accuracy and efficiency. And the intelligent algorithm model used in the fusion model is superior to other algorithm models. The overflow diagnosis accuracy of the fusion model on the test set samples reaches more than 98%, and the accuracy of the validation set is 94.25%. The content of this study provides guidance for drilling overflow diagnosis and model fusion methods.