Real-time monitoring and early warning of well leakage based on big data analysis

Abstract In petroleum drilling engineering operations, complex lost circulation accidents not only affect the efficiency of drilling operations, but serious lost circulation may cause wellbore failure. The occurrence of lost circulation accidents is affected by various factors such as formation conditions, engineering parameters, and operating dynamic parameters. The conventional focus of lost circulation research is to analyze the mechanism of lost circulation, but the data such as engineering parameters and operating dynamic parameters when lost circulation occurs are insufficiently utilized. At present, the field of drilling engineering has accumulated a large amount of historical drilling data, and the complicated occurrence of lost circulation accidents often has regional statistics. How to use big data technology to establish the correlation model between lost circulation and parameters, reason and analyze the main influencing factors of lost circulation, then use the established correlation model comparative analysis. After the data model comparative analysis, it can make different specifications of responses and early warnings for data anomalies with different weights, so as to reduce the impact on drilling operations while avoiding lost circulation accidents.