A Drilling Accident Early Warning Method Based on Time Recurrent Neural Network
A recursive neural network and accident technology, applied in neural learning methods, biological neural network models, predictions, etc., can solve the problem of inaccurate and comprehensive prediction of drilling accidents, achieve powerful parallel processing capabilities and practicality, and improve accuracy And timeliness, real-time requirements of high effect
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[0031] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.
[0032] According to one embodiment of the present application, the method for early warning of drilling accidents based on time recurrent neural network of this program includes:
[0033] S1. First, use the autoregressive model analysis method to predict the drilling characteristic value at a certain moment, and measure the difference between the predicted characteristic value and the real drilling data at that moment, there...
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