DocumentCode :
694821
Title :
A Process-Oriented Ontology-Based Knowledge Model
Author :
Yanhong Zhao ; Hongqi Li ; Liping Zhu ; Fengqi Tan ; Ying Wang
Author_Institution :
Coll. of Geophys. & Inf. Eng., China Univ. of Pet., Beijing, China
fYear :
2013
fDate :
7-8 Dec. 2013
Firstpage :
818
Lastpage :
823
Abstract :
With the rapid growth of knowledge resources, the production departments in the field of oil and gas exploration and development produce daily a great volume of result documents. Meanwhile, a large part of knowledge is stored in the experts´ brain as experience. How to spend less effort finding knowledge meeting users´ need and how to make effective use of the expertise to avoid knowledge loss become more and more important. This paper adopts a knowledge model which is composed by process model and ontology model in the subject of Well Site Deployment. In this knowledge model, the process model provides the detailed operation flow and data flow, the ontology model provides the evaluating standards and the operating standards. We build a web-based knowledge service platform based on this knowledge model, through which knowledge can be shared between experts and non-experts. Furthermore, users can reuse the knowledge and trace the existing work results of well site deployment and development by the platform. All of these can help the final users to improve the efficiency of decision making.
Keywords :
Internet; decision making; knowledge management; ontologies (artificial intelligence); petroleum industry; production engineering computing; Web-based knowledge service platform; data flow; decision making; experts brain; knowledge resources; oil and gas exploration; ontology model; operation flow; process model; process-oriented ontology-based knowledge model; well site deployment; Business; Computational modeling; Data models; Databases; Ontologies; Reservoirs; Knowledge model; Knowledge service; Ontology; Process model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
Conference_Location :
Guangzhou
Type :
conf
DOI :
10.1109/ISCC-C.2013.29
Filename :
6973693
Link To Document :
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