Research on Lost Circulation Risk Intelligent Identification and Processing System Based on CBR

Abstract Due to the large number of complex and uncertain factors in the drilling process, it is very difficult to identify and deal with the risk of lost circulation by establishing an accurate mathematical model, and the existing intelligent methods are difficult to acquire or require large sample data. In view of the defects, an intelligent decision-making method based on case-based reasoning is proposed, and a software system for intelligent identification and processing of lost circulation risk is developed. In this system, the lost circulation cases of oil fields in the past are represented as case forms in the case base. The design idea of the case retrieval model is to design an improved similarity calculation model for different types of attributes, based on the traditional instance similarity calculation model, which can effectively solve the information uncertainty. The system was tested by field data and the results show that the lost circulation risk identification and processing method can meet the application requirements of the drilling site, and can effectively improve the intelligent level of lost circulation risk management.