Real-time early warning of drilling overflow based on naive Bayes algorithm

If the overflow in the drilling process of high temperature and high pressure (HTHP) well isn’t identified in time, serious consequence will be caused. Existing overflow monitoring technology depends on downhole or surface tools, so it is time lagged to some extent. To solve this problem, this paper developed the real-time overflow early warning method based on naive Bayes and drilling big data. As for an area with a certain scale of drilled wells, the probabilistic relationships between the historical drilling overflow and the geological data, mud logging while drilling and wireline logging while drilling are analyzed, the prior probability calculation model of overflow and the condition probability calculation model containing six attributes of region, stratigraphy, lithology, torque, pumping pressure and rate of penetration (ROP) are established. The posterior probability of overflow is calculated based on Bayes theory. Thus, the function of real-time early warning is realized. It is indicated the overflow early warning method based on naive Bayes is more advantageous in terms of reliability, transmission efficiency and data accessibility. And its feasibility is verified based on actual cases.