Title :
Research on Intelligent Diagnosis and Processing System for Drilling Accident
Author :
Xu Yingzhuo ; Gao Xiaorong
Author_Institution :
Inst. of Comput., Xi´an Shiyou Univ., Xi´an, China
Abstract :
Because of many deficiencies of traditional drilling accident diagnosing and processing systems, for instance, these system were mostly based on static information from ground, so it was difficult to accurately distinguish the "down hole" accidents in real time, and they could not permit multi-user collaboration and share information. So an intelligent diagnosis and processing system for drilling accidents supported by computer networks is put forward to develop. According to levels and working environment of users, the architecture of this system is designed, which is generally divided into two levels: onsite and base level. Models of intelligent diagnosis and processing for drilling accidents are built by case-based reasoning techniques. And through Ajax technique, the asynchronous communication between the client and server is realized to increase the response speed of the server. On the basis of the above, combining the technology of Web Service, an intelligent diagnosis and processing system for drilling accidents is implemented. The system, which collected all kinds of accident\´s cases occurred in oil fields and could makes full use of all types of information (especially real-time information while drilling) as well as multi-domain experts\´ experience and knowledge, has self-learning function and can realize the diagnosis and processing for all kinds of drilling accidents. At the same time, the system provides an intact knowledge handbook of preventing and process accidents, as well as an information-sharing platform for multi-domain experts and technicians to make decisions collaboratively. Using the system can effectively improve diagnosis and processing accidents in terms of accuracy.
Keywords :
Web services; accident prevention; case-based reasoning; client-server systems; computer networks; information management; learning (artificial intelligence); oil drilling; petroleum industry; production engineering computing; Web Service; asynchronous communication; case-based reasoning techniques; computer networks; drilling accidents; information-sharing platform; intelligent diagnosis system; intelligent processing system; self-learning function; static information; underground engineering; Accidents; Artificial intelligence; Cognition; Decision making; Drilling machines; Real-time systems; Servers; Case-Based Reasoning; Diagnosing and Processing; Drilling Accident; Intelligence;
Conference_Titel :
Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4799-4262-6
DOI :
10.1109/ISDEA.2014.182