Research On The Expert System Of Cementing Quality Evaluation Based On Ontology

Cementing quality assessment is a complex and important task n oil exploration.Because It is of great significance for ensuring the life of oil and gas wells and environmental protection.However,for the many kinds of complex conditions,like diversification of geological,complexity of assessment,and the different need from many involved department.In order to help the cementing technicians evaluate the quality of well cementing.This paper proposes an expert system to evaluate and predict quality of well cementing base on ontology method.The ontology method is used to describe the knowledge of cementing quality and cementing quality rules.In the inference part,the ontology-based Bayesian network inference method is used.In the development aspect,the Protege platform is used to develop the ontology knowledge base and the ontology reasoning library.The BayesOWL framework adds the uncertainty to the ontology rule base and to inline the rules into the Protege platform through the plugin JessTab.Finally,this paper uses VS2017 to write the interface of the expert system,and verified it with experimental data.The verification results are consistent with the actual situation.The ontology-based knowledge base proposed in this paper has reusability and knowledge completeness.The Bayesian network inference method solves the problem that the ontology knowledge can’t express the knowledge uncertainty and fuzziness,so that it can be described in arbitrary probability form.